Social change, cultural evolution, weaving apprenticeship, and development: informal education across three generations and 42 years in a Maya community

Abstract

Analyzing three sets of video data collected in one Maya community, we examined apprenticeship and learning of backstrap loom weaving over three generations spanning the years 1970 to 2012. Like many cultural groups, the Maya of Chiapas are experiencing rapid sociodemographic shifts. Three generations of girls (N = 134) were observed at their looms: in the 1970 subsistence economy; in the transition to a commercial economy in the 1990s; and in 2012, when the commercial economy required formal education. Multilevel models showed that intergenerational sociodemographic change - increased time in school, greater involvement in the money economy, and decreased family size - changed weaving apprenticeship, which, in turn, was related to changes in characteristics of learners. In 2012, weaving learners received more explanations, praise, and body instruction from their teachers. Learners, in turn, asked more questions. However, these changes came at a cost - the gradual loss of weaving as an everyday subsistence practice and art form. Tracing intergenerational change over three generations, this study makes a unique contribution to an understanding of cultural evolution.

Introduction: the evolution of cultural transmission in a real-world setting

In this study, we use the case of the apprenticeship of Maya weaving, a central cultural practice with an ancient cultural tool, the backstrap loom, to empirically examine processes of cultural change, i.e., cultural evolution. Our methodology allows us to explore how ecological change produces historical change in cultural transmission, specifically, the intergenerational transmission of backstrap-loom weaving. We term the interactive teaching practices that produce intergenerational transmission of a skill the “proximal learning environment”. Intergenerational transmission is central to cultural continuity. It is also central to cultural evolution. When the interactive teaching practices central to cultural transmission change, cultural evolution takes place. Our study focuses on intergenerational change in the transmission of skill with a cultural tool - the backstrap loom.

The transmission of weaving know-how in three successive generational cohorts over a 42-year-period of rapid ecological change in a Zinacantec Maya community in Chiapas, Mexico formed a natural experiment to elucidate processes of cultural evolution through empirical study. More concretely, we explore the ways that ecological change at the macro-level of the community are reflected in the sociodemographic characteristics of individuals; these sociodemographic characteristics are components of the “distal learning environment”. This distal learning environment is then reflected at the micro-level of the proximal learning environment, which in turn influences the behavior of individual learners. The comprehensive theoretical claim of this research is that (1) changes in a community ecology are reflected in shifting sociodemographic characteristics of community residents. These sociodemographic characteristics constitute the distal learning environment for the next generation. (2) Shifts in the distal learning environment are reflected in corresponding adaptations in proximal learning environments, interactions between learner and teacher. (3) These, in turn, foster changes in learner behavior, that is, altered developmental pathways. In principle, although not in detail, this conception resembles Bronfenbrenner’s (1977) ecological systems theory with development affected by multiple levels going from the developing child’s immediate environment outward to the broader environment.

We studied the first generational cohort of Zinacantec Maya girls learning to weave in 1970 (Childs & Greenfield, 1980); we studied the second generational cohort in the early 1990s (Greenfield et al., 2003). In this article we introduce the third generational cohort, studied in 2012. The longitudinal study of three generations of learners, all observed in the same age range, provides a unique cross-cohort comparative design in comparative development. Most important to the research design of our natural experiment, each successive generation grew up in a different ecology, an environment with unique sociodemographic features. Therefore, we can isolate and differentiate the sociodemographic mechanisms that produced shifts in learning processes from Generation 1 to Generation 2 and from Generation 2 to Generation 3. By tracing intergenerational change in a key practice of cultural transmission in three different ecologies, over such an extended time span, we are in the position of making a unique contribution to a data-based understanding of cultural evolution.

Cross-sectional designs comparing different participants in different ecologies have provided valuable information suggesting behavioral effects of social change in Maya communities in Chiapas, Mexico (Esteban-Guitart et al., 2018; Manago, 2014). Our approach has been the longitudinal study of a single village (Greenfield et al., 2003; Maynard et al., 2015); this is a more direct design for studying the effects of social change on culture and human development (Greenfield, 2018). A longitudinal research design allows the empirical study of cultural evolution, an intrinsically longitudinal process, in a way that cross-sectional designs do not.

Social change from Gemeinschaft to Gesellschaft: Implications for cultural transmission

Like many cultural groups, the Maya of Chiapas are experiencing rapid socio-economic and demographic shifts in the context of globalization. These macro-level shifts involve a number of interrelated and synergistic shifts: the development of a commercial economy, urbanization, the expansion of formal education, and the augmented use of technology. We summarize this suite of interrelated characteristics with Tönnies’ (1957) term Gesellschaft. In all of these areas, the Zinacantec Maya community of Nabenchauk has moved in the Gesellschaft direction from a relatively isolated community based on subsistence activities such as corn agriculture and weaving. Using Tönnies’ term, we summarize these interrelated characteristics with the term Gemeinschaft.

Another characteristic not mentioned by Tönnies, but that is part of a subsistence agricultural economy, is large family size (Greenfield, 2018). In a Gemeinschaft ecology, more children are adaptive because families need their assistance in subsistence tasks (Kagitcibasi & Ataca, 2005; Lancy, 2012). In contrast, smaller families are adaptive in Gesellschaft environments where children cost money (Greenfield, 2004).

Besides large family size, Gemeinschaft ecologies have relatively high infant and child mortality rates, whereas Gesellschaft ecologies have relatively low infant and child mortality rates. This is in part because of technological developments, notably medical care and a supply of purified water. In the current article we document intergenerational reductions in family size and infant/child mortality as part of Nabenchauk’s transition to a more Gesellschaft ecology. As will be seen, smaller families are an element of the distal learning environment that has implications for the intergenerational transmission of backstrap-loom weaving.

In the present study, we will assess how each of these community-level shifts in the Gesellschaft direction plays out in our three cohorts of participants, studied over a period of 42 years. We will also test their predicted interrelationship through correlational analysis. Interrelated ecological conditions produce what Rogoff and colleagues call “constellations of cultural practices” (Rogoff et al., 2014).

The comprehensive theoretical claim of this research is that interrelated changes in a community’s sociodemographic characteristics, the distal learning environment, will lead to corresponding adaptations in proximal learning environments, the cultural practice of teaching girls how to weave on a backstrap loom. Altered teaching practices will, in turn, foster altered developmental pathways, shifts in learner behavior. An important implication is that learning environments are adapted to shifting macro conditions.

In our study of the first two generations, we documented the influence of the economic transition from subsistence to commerce on the intergenerational transmission of backstrap-loom weaving in the Zinacantec Maya community of Nabenchauk. Those generations spanned the period from 1970 to 1993 (Greenfield et al., 2003). We found that the main effect of participating in a commercial economy on the cultural transmission of backstrap-loom weaving was to make the learning process a more independent one, as working mothers were unavailable to help daughters.

The current article adds the study of weaving apprenticeship in the third generation, 21 years later. This is a longitudinal study of a community. By adding the study of weaving apprenticeship in the third generation, 21 years later, we extend the longitudinal reach of our community study of the evolution of cultural transmission, and we explore the role of two new ecological factors: first, the expansion of educational opportunity to high school and almost universal primary education; second, the introduction of the cell phone.

Expansion of formal education and the introduction of cell service

Nabenchauk added remote junior high school education (telesecundaria) to elementary school between data collection for Generations 1 and 2. Between data collection for Generations 2 and 3, two high schools were established in neighboring Zinacantec communities (Manago, 2015). In that same period, a federal program called Oportunidades began paying poor Zinacantec families 1500 pesos (US$130) every two months for each child in high school and 800 pesos (US$70) for each child in junior high school (Manago, 2015). Thus for Generation 3, secondary education through high school became possible. Most important, elementary school graduation became normative for girls for the first time.

How does this influence work in concert with another new Gesellschaft factor, mobile technology, to produce change in the informal educational process of learning to weave? By 2012, the year we collected third-generation data, cell service was newly available in the county seat of Zinacantan Center (Manago & Pacheco, 2019), the neighboring colonial city of San Cristobal, and other cities in Chiapas where residents of Nabenchauk bought and sold commodities (Greenfield et al., 2009). Does more extended school experience, in combination with mobile technologies, alter or undercut the transmission of weaving to the next generation? These were central questions for our study.

Intergenerational shifts in teacher behavior: The evolution of cultural transmission in the proximal learning environment

Intergenerational transmission takes place at the level of the proximal learning environment. In this study, the proximal learning environment consists of practices used to teach backstrap-loom weaving. Cultural transmission and the role of teaching is a major focus in the study of cultural evolution (e.g., Csibra & Gergely, 2011). Our unique contribution is to document, through behavioral study in the field, how a culturally central practice of teaching has shifted with ecological change. More specifically, we examine, by means of video recordings, the proximal learning environment for the acquisition of skill in backstrap-loom weaving, the traditional skill involving the most complex female learning. The next sections discuss elements of the proximal learning environment that are applicable to weaving apprenticeship.

Praise and criticism

Whiting and Whiting (1975) were the first to point out that “the performance of economic tasks and domestic chores that contribute to family welfare are…intrinsically rewarding” (p.179). Coppens and Alcalá (2015) have extended this analysis, pointing out that children are eager to “pitch in” to contribute to family endeavors. Under these circumstances, children do not require extrinsic reinforcement in the form of praise. At the time our first generation learned to weave, weaving clothes for self and family was a crucial survival skill and therefore intrinsically rewarding. In line with the Whitings’ observation and the analysis of Coppens and Alcalá, there were extremely few instances of teacher praise for our first-generation sample of 14 learners (Childs & Greenfield, 1980).

Alcalá et al. (2014) point out that, in indigenous populations of Mexico and Central America, children voluntarily “pitch in” with family and household tasks. However, in wealthier and more highly educated Mexican families, children are more often extrinsically reinforced for doing chores. As the education level rose across the generations and as store-bought clothing increased, making weaving a less important contribution to basic subsistence, we predicted that praise, a form of extrinsic reinforcement, would increase as a component of the proximal learning environment for weaving apprenticeship.

Indeed, praise is useful to recognize outstanding work or effort, important in an individualistic value context (Greenfield et al., 2000). In China, the intergenerational rise in levels of formal education and other features of a Gesellschaft ecology were associated with a perception that the current generation of mothers praised their children more than the prior two generations (Zhou et al., 2017). We expected the same intergenerational trend toward more learner praise as the Zinacantec ecology moved in the Gesellschaft direction over two generations - with an increasingly commercial economy and, in Generation 3, much expanded formal education.

In contrast with praise, criticism functions to bring everyone up to a normative standard, which is functional in a collectivistic culture adapted to a Gemeinschaft environment. Indeed, at the time of Generation 1, critical or disparaging statements concerning a weaving learner’s skill were much more frequent than instances of praise. As individualistic values rose in China, in concert with increased education and economic development, grandmothers judged that parents of the current generation of young children were criticizing their children less than the previous two generations of parents (Zhou et al., 2017). Because of parallel social trends in Nabenchauk, we expected the ratio of praise to criticism to rise in weaving apprenticeship across the three generations in our study.

Bodily instruction

In a prior study in the same community, we demonstrated that “with respect to the body techniques of weaving,…there are two kinds of learners: native and non-native. The native learner is endowed from birth with [cultural experiences] that aid in furthering the use of various body techniques in weaving. The non-native learner is at a disadvantage in this realm and needs more extensive instruction in learning to position and use the body at each step of the process” (Maynard et al., 1999, p. 383). We found that cultural practices shared by Zinacantec adults and young girls, such as kneeling to pat tortillas or balancing a tumpline to carry wood, provided bodily skills—to the point that Zinacantec girls in the first two generations needed very little instruction in body techniques when learning to weave (Maynard et al., 1999; Greenfield, 2004).

In sharp contrast, one of the authors, who had not had this prior bodily experience needed a lot of instruction about body technique from her Zinacantec weaving teacher—and such instruction, in the form of both verbalization and bodily manipulation, was spontaneously provided. In the third generation, the cultural practices that prepared bodies to weave at a backstrap loom had disappeared as commerce replaced subsistence in the economic environment. At the time the data were collected on the third generation, girls and women sat on chairs rather than kneeling on the ground; and charcoal stoves had replaced wood fires for heating and cooking. Without this bodily preparation, we thought that, like the author, Zincantec girls would require and receive extensive body instruction, both verbal and nonverbal. We also realized that girls attending school would need more help in the weaving process, particularly the bodily postures and movements, because, most likely, girls observed in 2012 had been too busy with school to learn to weave.

Teacher explanation

Teacher explanation is very important in formal education (e.g., Geelan, 2020 at the high school level; Penno et al., 2002 at the elementary school level). Among the Kpelle in Liberia, formal education was the only influence that developed children’s explanatory skills in cognitive experiments (Cole & Scribner, 1974). Hence, we thought that as weaving teachers acquired more formal education, the frequency of explanation in weaving apprenticeship would increase.

The evolution of the distal learning environment: Sociodemographic shifts

Many ecological or sociodemographic shifts are outside the direct transmission situation. They reflect community change but are not part of teaching and learning how to weave. These ecological shifts constitute the evolution of the distal learning environment and are, in our theoretical conception, the motor of cultural evolution. Our ethnographic observations indicated the evolution of the distal learning environment through the following five sociodemographic shifts:

(1) Girls’ schooling

We already knew that children’s schooling had increased across the three generations (Maynard et al., 2015). Our ethnographic observations indicated that girls were now as frequently going to school as boys.

(2) Mothers’ schooling

Ethnographic observations also had revealed that there were women in the community who had been to school.

(3) Commercial activity

We already knew that family involvement in commercial activity, as both consumers and merchants, had increased in each generation (Maynard et al., 2015).

(4) Family size and (5) mobile technologies

Our ethnographic work had indicated that as money and commerce became the economic basis of the community and agriculture declined, children were seen as costing money rather than contributing labor. Starting with mothers of the second generation there was therefore interest in birth control (Greenfield, 2004). Also relevant to family size, our ethnographic observations in Nabenchauk had indicated big uptake of cell phones by young people, as well as by those involved in buying and/or selling vegetables and flowers in different communities.

Smaller family size and mobile technologies are related to Gesellschaft conditions that extend social networks beyond the family (Manago & Pacheco, 2019; Newson & Richerson, 2009). Fewer kin-centered social networks are related to lower birthrates (Newson et al., 2005). Smaller family size reduces the need for sibling caregiving and is one reason more girls, especially first-born daughters, are attending school (Greenfield et al., 2009). These factors then were seen as part of the distal learning environment which led to girls focusing their education on school rather than weaving.

Intergenerational shifts in learner behavior: the evolution of cultural transmission from the learner's perspective

Weaving expertise

As an indicator of individual development adapted to a Gemeinschaft ecology, we used the learner variable of weaving expertise - the ability to weave increasingly difficult items. Because completing elementary school had become normative in the third generation, we expected weaving expertise to decrease for lack of time. Another factor that would also produce a decrease in weaving expertise was that selling one’s weaving was not as profitable as engaging in other types of commercial activity. An important difference between learning to weave and going to school is that the former takes place at home, whereas the latter takes place in a specialized location away from the home and family.

Question asking

As an indicator of individual development adapted to a Gesellschaft ecology, we used the learner variable of question-asking during weaving apprenticeship. On the level of learner behavior, question-asking is relevant to both weaving apprenticeship and school. Children’s question-asking is highly valued in school situations (Ronfard et al., 2018). However, it can be considered a mark of disrespect in more Gemeinschaft communities, such as immigrant agricultural workers in California (Delgado-Gaitan, 1994). In communities in which carrying out useful subsistence tasks is the emphasis—what Lancy (2012) calls the “chore curriculum” - responding to adults with action rather than words is valued. In the first generation of weaving learners, the learners asked no questions; instead, they focused on carrying out actions their weaving teachers suggested to them in the imperative mode. However, we thought that, as girls and their mothers acquired more school education across the generations, the influence of formal education might carry over to informal weaving education. The third generation was the first one in which graduating from elementary school was normative for girls (Maynard et al., 2015). Hence, question-asking during weaving apprenticeship was a cognitive behavior in which we thought that formal education would have a spillover effect on informal education, leading to an important behavioral difference between Generation 2 and Generation 3.

Hypotheses

Synergy in the distal and proximal learning environments

The theory of social change, culture, and human development (Greenfield, 2009) posits that, at each level of the theory, variables operate synergistically rather than independently. Hence we expected intercorrelated variables at both the macro and micro environmental levels.

1. Sociodemographic components of the distal (macro) learning environment will show positive intercorrelations among family involvement in commercial activities, use of mobile technologies, learner’s schooling, and mother’s schooling, as well as negative correlations with family size.

2. Components of the proximal (micro) learning environment will show positive intercorrelations among body instruction, teacher explanations, and teacher praise

Ecological changes on the macro-level: The distal learning environment

We tested several hypotheses about sociodemographic shifts across the three generations. These shifts were thought to reflect ecological changes in the community as a whole.

3. Girls’ schooling will increase significantly over the three generations. We had already demonstrated an increase in schooling across the three generations in the group consisting of both boys and girls (Maynard, Greenfield, & Childs, 2015). Because completing elementary school had become normative for girls for the first time in Generation 3, we expected girls' schooling to be consistent with this overall pattern and increase across the three generations.

4. Mothers’ schooling will increase significantly over the three generations. Because many of the children of one generation became the parents of the next generation, we also expected mothers’ schooling to increase across the generations. Research by Laosa (1978), Chavajay and Rogoff (2002), Chavajay (2006), and LeVine et al. (2012) had all shown that maternal education influences how mothers organize children’s informal learning activities out of school. Hence, the historical increase in maternal schooling became a component of our integrated model, linking shifts in distal learning environment to the proximal learning environment of weaving apprenticeship.

5. Family commerce will increase significantly over the three generations. We predicted that family commerce would increase over the three generations. Because commercial activity was facilitated by an elementary school education that allowed bookkeeping (Greenfield et al., 2009), we considered commerce to work synergistically with schooling as factors that could shift the proximal learning environment of weaving apprenticeship.

6. Textile commerce, which had increased from Generation 1 to Generation 2, would decrease in Generation 3. We already knew that textile commerce carried out by mothers and daughters had increased from Generation 1 to Generation 2. However, the foundation for all aspects of textile commerce was weaving and embroidering items to be sold. As schooling began to replace weaving and embroidery in the lives of Zinacantec girls in Nabenchauk, there was reason to believe that textile commerce would decrease in Generation 3.

7. Family size will decrease over the three generations. A declining birthrate would be in line with the concept of the demographic transition (Coale, 1989), a decrease in family size that occurs around the world when environments move from traditional to modern, in other words, move in the Gesellschaft direction. As will be seen, smaller families are an element of the distal learning environment that has implications for the intergenerational transmission of backstrap-loom weaving.

8. In the third generation, mobile technologies will be used. We included the use of mobile technology in our model of the distal learning environment, described later.

9. Infant and child mortality will decrease over the three generations. Our ethnographic observations indicated that residents in 2012 were making much greater use of medical facilities, both medical clinics and pharmacies, than had been the case for prior generations. In addition, purified water had become widely available in 2012 in the form of bottled water available for purchase in the village. Clean water had not been readily available at the time we studied Generations 1 and 2. These shifts were elements in the transition to a more Gesellschaft ecology.

Shifts in the intergenerational transmission of weaving: The proximal learning environment

The proximal learning environment for weaving consisted of the interactive processes shown in video recordings of girls learning to weave at home, i.e., the processes of weaving apprenticeship. Based on ethnographically observed changes in the distal learning environment, we tested the following hypotheses:

10. Girls will require and receive more instruction in body postures and movements in Generation 3. The reason for this hypothesis was the decline in Generation 3 of subsistence activities such as kneeling to make tortillas that provided practice in the bodily positions and movements required to weave at a backstrap loom (Greenfield, 2004). Furthermore, we hypothesized that schooling, which greatly reduces time available for subsistence tasks, would be related to the need for instruction in body postures.

11. Praise by weaving teachers will increase across the generations, as will the ratio of praise to criticism. As in our prior research on social change, we use the term praise to mean verbal approval of behavior and the term criticism to mean negative appraisals of behavior (Zhou et al., 2017). In our study of the first generation of weaving apprenticeship in Nabenchauk, we labeled these two concepts as positive and negative reinforcement (Childs & Greenfield, 1980). When an ecology moves from subsistence to commerce and formal education expands, as has occurred over recent generations in China, praise of children, a promotion strategy, is an aspect of the learning environment that increases while the frequency of criticism, a prevention strategy, declines (Higgins, 1998; Zhou et al., 2018). Because these ecological shifts have also occurred in Nabenchauk, we thought that this shift could be applicable to intergenerational shifts in weaving instruction in Nabenchauk—where, in the first generation, there had been a number of instances of criticism, but almost no instances of praise (Childs & Greenfield, 1980).

12. Explanations by weaving teachers will increase across the generations. This hypothesis was based on the importance of explanation in formal education, as described in the Introduction. It was also based on the idea and findings that the teaching techniques experienced in formal education transfer into informal education (Chavajay, 2006; Chavajay & Rogoff, 2002; Laosa, 1978).

Learner change

13. Weaving expertise will decline in the current generation. From Generation 1 to Generation 2, weaving skills and woven items expanded as textile creation became the first income-producing activity for Zinacantec females (Greenfield, 2004). However, as the commercial ecology developed further between Generation 2 and Generation 3, weaving became less important, while schooling, directly related to the language and math skills needed for commercial transactions, became more important. Because our weaving scale focused on subsistence items that did not require the new skills, a reasonable expectation was that weaving expertise would remain constant from Generation 1 to Generation 2, but decrease from Generation 2 to Generation 3.

14. Because schooling would compete with weaving, we predicted an inverse relationship between weaving expertise and school experience. In other words, girls would be weaving less because they were attending school more. Prior research was in line with this prediction. Indeed, in Mitontik, another Maya community in Highland Chiapas, universal schooling led to the almost complete disappearance of weaving apprenticeship (Zambrano, 2000). One reason for this inverse relationship between home-based weaving apprenticeship and school-based formal education is that “Schooling tends to withdraw people from their normal life and activities and locate them in specially designed institutions” (Obidi, 1995, p. 372). With increased school experience, members of an indigenous community in Michoacan, Mexico have come to value physical work less and academic work more than less schooled community members of the past (Correa-Chávez et al., 2016).

15. We predicted an increase in a trait adaptive in school: Asking questions. Asking questions is an important skill in maximizing school-based learning (Marx et al., 1999), and fewer questions are asked by students coming from a more tradition-oriented culture (e.g., Dkeidek et al., 2011). In cultures organized around vertical collectivism (i.e., social hierarchy), such as that of Mexican immigrants to the United States or people of sub-Saharan Africa, children’s questions can be seen in a negative light, as challenging parental authority (Delgado-Gaitan, 1994; Gauvain et al., 2013; LeVine, 1973). In pottery production, cross-cultural comparison within sub-Saharan Africa revealed a link between learner questioning, innovative designs, and commercial markets for the products (Wallaert-Pêtre, 2001). The Zinacantecs had moved away from tradition and toward innovation in their textile designs; parental authority had lessened as commercial activity had developed; and school-based education had increased across the generations (Greenfield, 2004; Maynard & Greenfield, 2008; Maynard et al., 2015). We therefore thought that questions during weaving apprenticeship would increase across the generations.

Multilevel model

16. Integrated model of changes in the distal learning environment, proximal learning environment, and learner behavior. We hypothesized that increased commercial activity, increased schooling of both the learner and her mother, and smaller family size across the three generations, augmented by the introduction of mobile technology in Generation 3, would alter the nature of the proximal learning environment for weaving apprenticeship: Girls would have greater need for and therefore receive more bodily instruction; teachers would use both explanations and praise more frequently as instructional techniques. These intergenerational shifts in the process of learning to weave would then be associated both with expansion of a learner behavior valued in school - asking questions - and the decline of weaving expertise so important in the subsistence ecology of traditional Maya culture.

Method

Participants

The study community was Nabenchauk, a Zinacantec Maya community in Highland Chiapas. The state of Chiapas, the most southernmost state in Mexico, is distinguished by being majority Maya. The community is connected to the colonial city of San Cristobal de Las Casas by the Pan American Highway. It is currently about a 45-minute drive from Nabenchauk to San Cristobal.

Participants were 134 girls and their weaving teachers (mothers, grandmothers, aunts, cousins, and sisters) in three generations. They came from 80 nuclear families; all had homes in Nabenchauk. In the first generation, studied in 1969 and 1970, Nabenchauk, population about 1500, was a mainly subsistence ecology, with corn grown for both home consumption and sale. Most clothing was woven by female members of the community. One-room houses were built by community members. In the second generation, studied in 1991 and 1993, the economy had made a major shift toward a commercial ecology; its population had grown to about 3,000. The advent of NAFTA on January 1, 1994 flooded Mexico with cheap corn and almost immediately eliminated the growing of corn, thus accelerating the transition to an economy based on money and commerce. By the time of the third generation, studied in 2012, formal education for indigenous children had been greatly expanded and families were paid on a monthly basis to keep their children in school. By 2012, Nabenchauk’s population had again grown, reaching about 4500 inhabitants (Maynard et al., 2015).

Our focus is learning how to weave on a backstrap loom. Weaving apprenticeship was carried out at home and was done exclusively by female members of the community. The backstrap loom and the learning context are shown in two photographs later in this article (Figure 1). Our participants included 14 girls in Generation 1, 58 girls in Generation 2, and 62 girls in Generation 3. Participants in Generations 2 and 3 were descendants of earlier generations (typically a daughter, granddaughter, or niece of an earlier participant). The girls ranged in age from 3 to 22 years. The mean age across the generations was 11.47 years; there was no significant difference in the mean age among the generations (F (2, 131) = 1.521, p = .222). The mean age in Generation 1 was 10.78; for Generation 2, mean age was 12.18 years; for Generation 3 mean age was 10.95 years. The first generation was studied in 1970, the second generation in 1991 (almost all) or 1993, and the third generation in 2012. (The 1993 participants were a few girls judged by their mothers too young to weave in 1991.) The girls in each generation ranged from first-time weaver to expert.

Weaving teachers and helpers also participated in the videotaped sessions on the backstrap loom. Helpers differed from teachers in that they were younger than the weaving learner and, in contrast to the teachers, did not know how to weave themselves. In a total of 26 cases across all three cohorts, there was no teacher or helper; the weaver wove independently. In 17 of these 26 cases the weaver was already an expert weaver so clearly did not need a teacher or helper. Weaving expertise was assessed by asking whether the girls had ever woven five different items of varying difficulty. An expert weaver was defined as someone who had woven all or most of these items, including one or two of the most difficult items (pok mochebal shawl, skirt).

For the remaining 108 girls, each girl’s mother was included as a teacher in 66% of the cases. Most frequently the mother was the sole teacher/helper. But sometimes another member of the family, most frequently a teenage daughter, also participated as a teacher or helper. In 13% of the 108 cases, a teenage girl served as the sole weaving teacher or helper. Our findings from Generation 1 and Generation 2 indicated that an increase in teenage teachers in Generation 2 was associated with the creation of innovative textile designs (Greenfield, 2004). Only in the last generation (videotaped in 2012) did a few grandmothers (N = 4) serve as the sole weaving teacher for their granddaughters. We think that this is because mothers in that generation were too busy with their commercial activities to either weave or help their daughters learn to weave.

Family tree cards made by the third author in 1969 and 1970 (and continued by all authors at later time points) made it possible for us to locate the descendants of earlier participants when we returned to the field for research in 1991, 1993, and 2012. Most were living in Nabenchauk; a few visited Nabenchauk on the weekends, where they still had a house and could participate in our study. All the direct descendants of the earlier generations who were old enough to weave agreed to participate.

Connecting to the community

Two of the authors started out as members of the Harvard Chiapas Project, a National Science Foundation funded project to give Radcliffe and Harvard students field experience in Chiapas. The project was led by Harvard Anthropology Department Professor, the late Evon Vogt. When Greenfield and Childs started collaborating on research in Nabenchauk, Childs had already participated in the Harvard Chiapas Project a summer earlier and spoke fluent Tzotzil. All members of the Harvard Chiapas Project were given Tzotzil instruction before leaving for Chiapas.

A senior member of the Harvard Chiapas Project picked out our local assistant, Xun Pavlu, because he had an unusually large network of family and co-godparents (comadres and compadres); this anthropologist knew that our research required larger samples than the more ethnographic research that other members of the Harvard Chiapas Project were doing.

When we returned to study the second generation after 21 years, Xun Pavlu again assisted us in the research; again his main role was participant recruitment and accompanying us to the homes where we made our videotapes of girls at different stages of learning to weave. This time though, because our intergenerational comparison required us to recruit descendants of the prior generation, we used the family tree cards made by the third author to direct Xun’s recruitment efforts to particular girls, descendants or godchildren of our original participants. Maynard joined the research in the data analysis phase after two generations of data had been collected; she is also a fluent Tzotzil speaker. Greenfield is less fluent, but can use Tzotzil for daily life. Authors Maynard, Greenfield, and Childs also speak Spanish, which was especially useful in the neighboring city of San Cristobal, where they each spent almost all of their nights. Maynard and Childs learned how to weave on a backstrap loom, which enabled them to code the video data of girls learning to weave.

By the time of our third-generation data collection in 2012, Xun Pavlu had died and one of his daughters-in-law, Maruch Ch’entik took over his role of participant recruitment. Maynard took the lead in collecting the 2012 video data of the third generation learning to weave. Our relationships with two extended families, who helped us beyond simply being participants, established bonds that were cemented when we became co-godparents. Because the limit of girls’ formal education in the community was 7^th grade, and even that was a rare accomplishment, community members could not serve as research assistants or be consulted about research design in the way they would be in the United States. However, three generations of Xun Pavlu’s family have provided input and pilot data for all research procedures.

Procedure

We used video and interview data that we had collected in 1970 and the early 1990s for the first two generations. The interview data for the first two generations had already been entered into a master SPSS database, to which the 2012 data (see below for procedure) were added. The videos of weaving apprenticeship for the first two generations, plus the new videos from the third generation, were coded for the variables of interest in this study, as elaborated below.

For the 2012 participants, we obtained informed consent from a parent and assent from minors, as approved by the University of Hawaìi Institutional Review Board Approval #CHS 20233 and the UCLA Institutional Review Board Approval #12-001084. For each generation, we videotaped a session of the girl weaving or learning to weave. Procedures approved by UCLA's IRB were also in place at the time the Generation 2 data were collected. IRBs did not exist at the time the Generation 1 data were collected.

Recordings were made in the family courtyard, or occasionally in the home, if it was raining. Our local assistant, the late Xun Pavlu, introduced us to the families and accompanied us to almost all recording sessions. When setting up appointments, Xun told the prospective participants that we were interested in watching girls learn to weave. It was completely up to the participant and her family whether or not a teacher would also be involved and, if so, who the teacher would be. Video recordings of these weaving sessions were the source of our information about the proximal learning environment for weaving apprenticeship and about learner behavior in the apprenticeship process.

We used recording equipment that was available in each time period. In 1970, we used the first Sony portable black-and-white reel-to-reel video recorder. In 1991 and 1993, we used a Sony Hi-8 color video recorder. In 2012, we used a Canon HD color video recorder. For the first generation, we used an external microphone set up under the loom. In 1991, 1993, and 2012, we used radio lavalier microphones worn by the weaving learner and her teacher or helper, if there was one. All sessions were recorded in Tzotzil, the native language of the participants and the language of the research team’s interactions with participants. For all cohorts, participants were given a photograph of themselves and a small payment for their time. For the second generation, we experimented with giving them a recording of themselves weaving; however, monetary payment was preferred, so monetary payment was substituted.

In addition to the recordings, there were several sources of detailed demographic data: semi-structured interviews by our research team in 1970, 1991, 1993, and 2012, and a Stanford Medical School survey of the community done in the summer of 1991. Participants and their mothers were interviewed about their sociodemographic environment, i.e., the distal learning environment, and about the participant’s weaving expertise. This information was integrated into the analysis.

Assessing the distal learning environment

Based on the semi-structured interviews, our analysis of generational change utilized the following components of the distal learning environment: girls’ and mothers’ schooling, family involvement in commerce, textile commerce, family size, infant and child mortality, and mobile technologies. Other sociodemographic elements were part of the interview, but not used in the present article.

Girls’ and mothers’ schooling

In semi-structured interviews carried out in participants’ homes we asked each girl and mother about the schooling that each had at the time of the study. We recorded answers in years, including kindergarten as one possible year of schooling.

Family commerce and textile commerce scales

In order to test our hypothesis that involvement in commerce was a significant change in the distal learning environment, we used interview and Stanford survey data to create a family-commerce scale and a textile-commerce scale. Family commerce included activities as both seller and consumer. Some examples of family commerce are: selling agricultural products, owning a car, and owning a number of consumer products ranging from small electric appliances to small refrigerators. The scale had 15 items; the score consisted of the percentage of commercial activities in which family members participated or items the family possessed.

Some examples of textile commerce activities are: selling weavings, winding weaving thread for pay, weaving on order, embroidering on order, and selling thread. The scale had 12 items; the score consisted of the percentage of textile commerce activities in which mother and daughter participated. Table 1 presents a complete listing of the items in the family-commerce and textile-commerce scales.

Table 1. Items used in the commerce scales.

Textile commerce	Family commerce
Learner sells weaving	Participating child sells agricultural products
Learner winds thread for pay	(other than peaches)
Learner sells thread	Participating child sells peaches
Mother sells weaving	Participating child sells flowers
Mother sells thread	Participating child works for wages
Mother weaves for others on order	Participating child works in a shop
Mother sews for others on order	Child is a carpenter
Learner weaves for others on order	Father participates exclusively in a modern activity
Learner sews for others on order	(commerce, driving, construction, carpentry)
Family owns a sewing machine	Mother sells peaches
Learner draws on order for embroidery	Mother sells tortillas
Mother draws on order for embroidery	TV in household
	VCR/DVD player in household
	Radio, cassette, CD player, or stereo in household
	Family owns a shop
	Family runs a mill
	Family owns a vehicle

Note: Percentage scores for each scale are calculated by dividing the number of affirmative items by the total number of items in that particular scale.

Mobile technology scale

In order to test our hypothesis that use of mobile technology was a significant change in the learning environment, we used interview data to create a mobile technology scale. This four-item scale included whether the participant had and used a cell phone, and whether the participant had or used a camera, video-recorder, or internet via the cell phone. Each of these items just required a yes-no response; the “yes” items were totaled for a score.

Family size

This information was gleaned from our family tree cards, which we added to in each generation of participants. The information about family composition was gathered during semi-structured interviews in which we asked about the names, birth dates and/or ages of each member of a nuclear family. This record allowed the determination of the sibling set in each generation. We collected data on all the children in the family, living and deceased, at the time of the data collection. For these analyses, we used, for each participant, the total number of children in their sibling set, including those deceased, because we were interested in overall birth rates.

Infant and child mortality

We used interviews, recorded on our family tree cards, as the source of this variable. These cards noted when any child in a particular nuclear family had died at any age before our interview.

Coding the video recordings

Video recordings from each of the three cohorts were extensively coded by Maynard and Childs. The foundation of the coding system lay in the fact that community members had taught both coders backstrap loom weaving and that these two authors had not only learned to weave, but they had also watched many Zinacantec girls being taught how to weave during the video recording sessions. By the third generation, Maynard already knew all the families involved in the study.

The basis for creating and identifying verbal codes lay in the fact that the coders were both fluent in the Maya language of Tzotzil. The limitations of formal education in the community meant that the very concept of coding categories would not be meaningful to our local assistants, either to expert Zinacantec weavers, or to weaving learners. Coding could not be done blind to the hypotheses because both qualified coders were also authors of the research, involved in collecting and/or analyzing all three waves of data collection, and were therefore familiar with the hypotheses.

All the video recordings from the first two cohorts were re-coded for our new variables of interest. We coded the first cycle of the weaving lesson because this cycle is difficult, providing the opportunity for questions, errors, and other variables of interest. By the first cycle, we mean from the moment of the insertion of the first bobbin until the moment of the insertion of the third bobbin. The first-cycle segments ranged from 0:41 − 13:29, with an average of 3:26. As our unit of analysis was the activity, in every case, the entire segment was coded.

Assessing the proximal learning environment

Our analysis of generational change utilized the following components of the proximal learning environment manifest during the first cycle of weaving in the weaving video: body instruction, teacher praise, teacher criticism, and teacher explanations.

Body instruction

Body instruction given to girls was defined as weaving teachers providing verbal and nonverbal instruction about what to do with the body in order to weave. Verbal instructions included “Kneel!”, “Sit up straight!” and “Lean back!”. Nonverbal instruction included moving the learner’s body, including moving the hand, pressing the back forward, or demonstrating how to lean forward properly.

Praise and criticism

For all three generations, praise was operationally defined as verbal approval of behavior during weaving. It included supportive verbal comments such as “Good!” For all three generations, criticism was operationally defined as negative verbal appraisal during weaving. It included comments such as “You don’t know how!” Because of its low frequency, criticism was not able to be used as a variable in itself. However, the ratio of praise to criticism and its change over the generations was explored.

Teacher explanations

Explanations were defined as explaining why a particular action happened, why the cloth was a certain way, or why the girl needed to do something. Explanations included “Just like that already because it is tight already.” and “Because it is thin, I said.”

Assessing the learner

To assess the learner, we coded, during the first cycle of weaving, questions asked by the girl. In the semi-structured interview that took place during the session, we asked the girl’s age and interviewed her about her weaving experience, obtaining information for our scale of weaving expertise.

Questions

We noted and quantified questions asked by girls. Questions included “Where does this go?” “Why does this go here?” and “Like this?” As illustrated by this last question, the nonverbal element of intonation was utilized to identify a question, even when question syntax was not used. Concerning overt nonverbal questions - “gestures which serve to elicit a verbal response such as questioning glances, raised eyebrows, shoulder or hand shrugs, and puzzled facial expressions” (Kearsley, 1976, p. 357), if these occurred at all, they were extremely infrequent and were not coded. “Covert nonverbal questions are internally directed questions we ask and answer ourselves” (Kearsley, 1976, p. 357). Such nonverbal questions were of course invisible and therefore could not be coded.

Weaving expertise

In the semi-structured interview, we asked about girls’ weaving experience, noting whether they had woven items of increasing difficulty including a basic small cloth, two different shawl patterns worn by girls and women, a skirt, and the poncho worn by boys and men. Weaving expertise was a six-point scale. Starting with 1 (no experience), the weaver received one additional point for having woven each of the five items. Girls’ weaving expertise ranged from zero to five items, with a mean of 1.69 items woven. Fifty-one girls had no prior experience and 28 of them had woven only one item, which would generally have been the basic small cloth. It is important to note that the items contain a large range of difficulty, both in pattern and in size. The patterns are put in at the warp-winding stage (and can be produced by a different weaver), so they are not relevant to weaving difficulty. However, size is a very relevant variable - larger items are more difficult to handle because of weight and balance issues, given that the weaver is part of the loom frame in backstrap-loom weaving.

Because of their large size, skirts would generally be the most difficult of the five items to weave. This scale was our measure of weaving expertise.

Age

This variable was also assessed in the semi-structured interview.

Kneeling

The kneeling variable was coded from the videos. It had three values: kneeling throughout the coded segment, kneeling for part of the time; and using other body positions the whole time.

Reliability

We calculated reliability of the video coding by comparing the two coders’ assessments of each variable sampling each generation, for a total of 22 learners. We present here reliability for the variables referred to in this article. The reliability of the lengths of segments was assessed by Pearson correlation coefficients: r = 1.0, p = .000. The reliability of the other observed behavioral variables was assessed by the Kappa statistic. Kappas were calculated for teacher explanation (K = 1.0) praise (K = .645), criticism (K = .68), body instruction (K = .653), learner questions (K = .904), and learner kneeling (K = 1.0). These Kappas show moderate to perfect agreement (Landis & Koch, 1977).

As mentioned earlier, both coders were themselves taught to do backstrap loom weaving in Nabenchauk, so they understood, through their own experience, the local weaving apprenticeship process. They also understood how to input the variables into an electronic database. This latter skill component, necessary for coding, was not available in the community itself because of limited availability of formal education.

Composite distal and proximal learning environment variables utilized in the mediation model

In creating composite variables, all of the component variables were standardized, as they all had different scales, and the standardized values were averaged in each composite variable. Component variables were included in each of the composite variables if they were found to be correlated with at least one of the other component variables (with all relations, significant or not, being in the expected direction), and, for distal and proximal learning environment variables, with generation and/or at least one of the learning change dependent variables.

Why composite variables?

Although there is no clear method of determining the optimal sample size for bootstrap methods for mediation (Fritz & MacKinnon, 2007), in particular mediation with multiple mediators (MacKinnon et al., 2004, Lockwood, & Williams, 2004), the bootstrap mediation used in this study was found to be the best of the mediation methods as well as the one that allowed for the smallest samples, even under 60 participants for a single mediation path with large effects (Fritz & MacKinnon, 2007; MacKinnon et al., 2004). Given the serial mediation used in the current study, we assumed that a larger number of participants would be necessary, although the addition of variables in some cases might actually increase the power without the need to have a larger sample (MacKinnon et al., 2004). Nevertheless, we thought the most prudent approach and one that would allow for the clearest explanations would be to limit the number of mediating variables in the model. Rather than testing each of the component variables as mediators, and specifically testing the serial effect of each of the sociodemographic variables on each of the learning environment variables, and, in turn, the effect of each of the learning environment variables on the dependent variable of girl’s question asking, we chose to create a single composite sociodemographic distal learning variable and a single composite proximal learning variable. Composite variables are also in line with Greenfield’s theoretical formulation of the equipotentiality of all Gemeinschaft and Gesellschaft variables (Greenfield, 2009). However, the relationship among components of the distal and proximal learning environments is put to empirical test by correlational analyses presented at the beginning of the Results section.

Composite distal learning environment variable

This variable was created by standardizing and averaging each of the sociodemographic variables of mother’s schooling, learner’s schooling, family participation in commerce, access to mobile technology, and size of sibling set (reverse coded), and then averaging the standardized variables together. Participation in textile commerce was not used in the composite variable because of its expected curvilinear relationship to generation.

Each of the component standardized variables was found significantly correlated with generation (p < .001: positive correlation of generation with commerce, mobile technology, learner’s schooling; p = .01: positive correlation of generation with mother’s schooling; p < .001: negative correlation of generation with family size).

Standardized scores for commerce, mobile technology, learner’s schooling, and mother’s schooling were also positively correlated with learner questions; while family size was negatively correlated. All of these correlations reached the .03 level of significance or better.

The same variables comprising the distal learning environment had the opposite relationship with weaving expertise. Negative correlations of weaving expertise with mother’s schooling and mobile technology, plus a positive correlation of weaving expertise with family size reached the .03 level of significance or better. Correlations of weaving expertise with learner’s schooling and family commerce were negative as predicted but did not attain statistical significance at the .05 level.

Composite proximal learning environment variable

This variable concerned the specific learning of weaving; all component variables were coded from the weaving videos during the first cycle of weaving (insertion of first two crosswise [weft] threads),

All standardized components of the proximal learning environment, including teacher explanations, showed significant positive correlations with learner questions and generation (p < .001). All standardized components of the proximal learning environment showed negative correlations with weaving expertise and generation. The negative correlations were all statistically significant except for teacher explanations (body instruction: p < .001; praise: p = .03; generation: p = .02).

The composite variable was created by standardizing the number of times the teacher offered praise, the number of times the teacher provided explanations, and the number of times the teacher gave body instructions, and then averaging the standardized variables.

Analyses

Differences between the three generations were tested by means of analyses of variance, with covariates such as age where appropriate. Effect size was estimated using partial eta squared. .01 was considered a small effect size, .06 a medium effect size, and .14 a large effect size. Because of unequal variances and sample sizes in the three generations of weaving learners, the Games-Howell test for multiple comparisons was used to assess which generations were significantly different from each other. In the case of one proximal variable, the ratio of praise to criticism, a chi-square test was used. To test whether schooling competed with weaving, a correlational analysis using Pearson’s r was carried out.

For the multilevel model, a test of serial mediation was accomplished through the program PROCESS version 3.1 (Hayes, 2018) which uses bootstrapping, allows for tests of multiple mediators, and allows for testing a model in which mediators are ordered. A mediation is considered to be significant if the CI of test results does not include zero.

Results

We begin with the macro level of distal learning environment and the microlevel of proximal learning environment. We see each as each composed of a suite of interacting and synergistic variables.

Hypothesis 1: Ecology: Sociodemographic components of the distal (macro) learning environment will show positive intercorrelations among family involvement in commercial activities, use of mobile technologies, learner’s schooling, and mother’s schooling, as well as negative correlations with family size

Table 2 shows the correlations among the standardized sociodemographic variables used to construct the composite sociodemographic distal learning variable. This table shows that these variables are moderately intercorrelated. Most of the correlations are statistically significant, but each variable also explains unique variance. These correlations are in line with the theory of social change, culture, and human development (Greenfield, 2009); it posits that, at each level of the theory, variables operate synergistically rather than independently.

Table 2. The distal learning environment: Correlations among sociodemographic characteristics - number of children, commerce, mobile technology, own schooling, and mother’s schooling.

	Number of children	Commerce	Mobile technology	Girl’s schooling	Mother’s schooling
Number of children	–
Commerce	−.23**	–
Mobile technology	−.26**	.50^****	–
Girl’s schooling	−.20*	.32***	.35***	–
Mother’s schooling	−.31***	.11	.11	.10	–

*p < .05; **p < .01; ***p < .001; ****p < .0001.

Hypothesis 2: Components of the proximal (micro) learning environment will show positive intercorrelations among body instruction, teacher explanations, and teacher praise

As with the sociodemographic variables, the proximal learning environment variables are, as predicted, moderately intercorrelated (Table 3). All correlations are statistically significant, but each variable also explains unique variance. Once again, these correlations are also in line with the theory of social change, culture, and human development (Greenfield, 2009) that, at each level of the theory, variables operate synergistically rather than independently.

Table 3. The proximal learning environment: Correlations among body instruction, teacher’s explanations, and teacher’s statements of praise.

	Body instruction	Teacher explanations	Teacher praise
Body instruction	–
Teacher explanations	.36^****	–
Teacher praise	.40^****	.30***	–

***p < .001; ****p < .0001.

Sociodemographic changes across the three generations: the distal learning environment

First, we were interested in demonstrating how the distal learning environment had changed over the three generations, so we examined engagement with schooling, involvement in commerce and textile commerce, and family size. Because the details of this historical process are crucial to the theoretical framework and the statistical models being tested, we include these shifts as part of the results, rather than as “background” factors placed in the Participants subsection of Method.

Hypothesis 3: Girls’ schooling will increase

We were interested in the endpoint of schooling for most girls. Because post-primary education was very rare, we analyzed the schooling of girls age 13 years and up. We found that girls’ schooling went up significantly over the three generations: Using just participants age 13 and up (F (2, 55) 25.82, p < .001, partial eta squared = .48, large effect size). A Games-Howell post-hoc test for multiple comparisons indicated that the difference between Generation 1 and Generation 2 was significant at less than .05, whereas the difference between Generation 2 and Generation 3 was significant at less than .001. Controlling for age as a covariate, schooling still went up significantly across the generations (F (3, 54) = 30.76, p < .001, partial eta squared = .53, large effect size). The mean years of schooling for girls ages 13 and up were: Generation 1 (0), Generation 2 (.60), and Generation 3 (4.76). No girls 13 and up had ever been to school in 1970. In 1991 and 1993, the range for schooling was zero to six years. In 2012, the range was zero to 9.5 years. The increased range in Generation 2 indicated that some girls were completing elementary school, which had become functional for carrying out commercial activities. The still greater range in 2012 reflected the fact that that at least one girl had received some secondary education in a neighboring Zinacantec community, a possibility that had not been there one generation earlier.

Hypothesis 4: Mothers’ schooling will increase

There was a small increase in mothers’ schooling, which was statistically significant F (2, 131) = 3.51, p = .03, partial eta squared = .05, a small effect size). Mothers’ mean schooling in Generation 1 was 0, while it was .36 years in Generation 2, and .84 years in Generation 3. A Games- Howell test indicated that the significant increase occurred between Generation 1 and Generation 2 (p = .004). The increase between Generation 2 and Generation 3 was not statistically significant.

In 1970 (Generation 1), not one mother had any schooling. In the early 1990s (Generation 2), the range went from zero to three years of school. In 2012 (Generation 3) the range of mothers’ school experience went from zero to six years. Again, the range is more telling than the means because it signals increased educational opportunity. One can also see that, as schooling opportunity expanded, daughters in the youngest generation had much more opportunity than their mothers had had.

Hypothesis 5: Family commerce will increase across three generations

Family involvement in commerce went up over the three generations (F (2, 131) = 37.62, p < .001, partial eta squared = .37, a large effect size). Although the increase from Generation 1 to Generation 2 was the largest (Games-Howell, p < .001), involvement in family commerce continued to go up from Generation 2 to Generation 3 (Games-Howell, p = .02). Mean commercial participation in Generation 1 was 0, while it was 3 out of 15 items in Generation 2 and 4 out of 15 items in Generation 3. The range was zero in Generation 1, 0 to 4 in Generation 2, and zero to 4 in Generation 3. The fact that the range stayed constant while the mean increased in Generation 3 shows that the variety of commercial activities had remained constant, but more residents of Nabenchauk were engaging in them.

Hypothesis 6: Textile commerce, which had increased significantly from Generation 1 to Generation 2, would decrease in Generation 3

As expected, the overall ANOVA indicated a significant change across the generations (F (2, 130) = 8.89, p < .001, partial eta squared = .12). Our means for textile commerce show that, in 1970, the average weaving learner was not involved in any type of textile commerce, and the range was zero. In the early 1990s, the average weaving learner had participated in 4 out of 12 possible types of textile commerce; the range was 0 to 10. In 2012, the average weaving learner had participated in only two or three types of textile commerce; the range was zero to nine. The Games-Howell test indicated that the increases in textile commerce from 1970 to the early 1990s and 2012 were significant at the .001 level, as expected. While the expected decrease from the early 1990s to 2012 took place, it did not attain statistical significance.

Hypothesis 7: Family size will decrease across the generations

Family size decreased significantly over time (F (2, 130) = 10.944, p < .001, partial eta squared = .144, a large effect size. The mean number of children in the family was (to the nearest whole number): Generation 1: 7; Generation 2: 5; Generation 3: 4. The significant difference, according to the Games-Howell test, is between Generation 2 and Generation 3 (p = .001).

The range of the number of children in the family is also interesting. The ranges are as follows: Generation 1: 1-13; Generation 2: 1-10; Generation 3: 1-8. Range is probably more informative than mean because young families in each generation were likely to add children in the future.

Hypothesis 8. Infant and child mortality will decrease across the generations

A one-way analysis of variance showed that there was a significant decrease in infant and child mortality from a mean of almost 1 child per nuclear family in Generation 1 to a mean of about 1 child per 3 families in Generation 2 to a mean of about 1 child in 30 families in Generation 3 (F (2, 130) = 7.261, p = .001, partial eta squared = .100, medium effect size) . Using the Games-Howell Test, the only significant difference was the decline in infant and child mortality from Generation 2 to Generation 3 (p = .006). The range was from zero to five child deaths per family in Generation 1, zero to four child deaths per family in Generation 2, zero or one child death in Generation 3.

Hypothesis 9. Mobile technologies will be used in Generation 3

There were no mobile technologies in Generations 1 or 2. In sharp contrast, mobile technologies were prevalent in Generation 3. The mean for Generation 3 was between one and two out of four items. The range went from zero to four. A significant ANOVA (F (2, 125) = 37.370, p < .001, partial eta squared = .374, a large effect size) and a post hoc Games-Howell test showed that showed that the Generation 3 differed significantly from Generation 1 and Generation 2 (p <.001).

Historical shifts across three generations: Changes in the proximal learning environment

Hypothesis 10: Girls would require more instruction in body postures and movements in Generation 3, compared with Generations 1 and 2

During the first weaving cycle, we counted verbal and nonverbal body instructions as well as instructions that were both verbal and nonverbal. There was more total body instruction across the historical periods (verbal, nonverbal, and both together). F (2, 130) = 4.22, p = .017. partial eta squared = .060, medium effect size. Means are Generation 1 = .46, Generation 2 = .47, Generation 3 = 1.53. These means translate to about half the learners receiving no body instruction in Generation 1 or 2 and, on average, learners in Generation 3 each receiving two or three instructions concerning body posture or movement. The range went from 0 to 4 instances of body instruction in Generation 1, 0 to 6 instances in Generation 2, and 0 to 17 instances in Generation 3.

Body instruction and kneeling

We analyzed an example of the body instruction given to a weaver at age 9 years in 1991 and compared it with her daughter at the same age (See Figure 1 and its explanatory caption). In 1991, PP was able to kneel correctly for a long period of time, and her mother did not give her instruction in how to kneel properly because such instruction was not necessary. But in 2012, PP’s daughter E was unable to kneel, complaining that her legs hurt, and her grandmother, PP’s mother, gave her granddaughter a number of prompts to position herself properly. We attribute the inability to kneel to the fact that PP grew up kneeling around the fire to make tortillas and carry out other activities. Small chairs were preferentially allocated to the males in the family. But daughter E grew up with tables and chairs; she lacked experience kneeling. It is known that to maintain the ability to kneel requires regular experience in kneeling growing up (Bolger, 2010; Molleson, 2007/2016).

For the sample as a whole, all learners kneeled for the whole analyzed weaving segment in 1970. In both the 1990s and 2012, a few girls deviated and used other positions while weaving. However, this was still a minority pattern (4 out of 58 in the 1990s, 5 out of 62 in 2012). Hence, chi-square tests (Preacher, 2001) did not achieve statistical significance for generational change in weaving position.

Figure 1. (Top): This is PP at age 9, kneeling to weave in 1991. PP has never been to school, and she grew up kneeling, for example, while making tortillas. Note how she is rising on her knees with her feet straight out in back of her.

(Bottom): This is her daughter E in 2012, also age 9. E has been going to school since preschool and has not learned to weave. This is her grandma CM trying to teach her for our study. But notice the body position. At 5:38pm, she is kind of kneeling but with her feet splayed out. But it is too uncomfortable for her and 8 minutes later (at 5:46), she is sitting.

Hypothesis 11: Praise by weaving teachers would increase across the generations, as would the ratio of praise to criticism

Confirming this hypothesis, we found that weaving teachers gave more praise across the three historical periods (F (2,131) = 5.79, p = .004, partial eta squared = .081, medium effect size). More meaningful than means is the intergenerational increase in the number of weaving teachers who gave any praise at all. In Generation 1, not 1 weaving teacher out of 14 praised the learner during the first cycle of weaving. In Generation 2, 5 out of 58 teachers praised the learner. In Generation 3, 21 out of 62 teachers praised the learner during the first cycle of weaving. The Games-Howell indicated that the statistically significant difference was between Generation 2 and Generation 3. In Generation 2, the range was zero to three instances of praise; in Generation 3 the range was zero to eight. In addition, in accord with the hypothesis, the ratio of praise to criticism increased significantly across the three generations (Chi-square = 12.11, df = 2, p =.002).

Hypothesis 12: Explanations by weaving teachers will increase across the generations

Explanations by weaving teachers went from none in Generation 1 to 8 explanations provided by a sample of 58 weaving teachers in Generation 2 and 9 explanations provided by a sample of 62 weaving teachers in Generation 3. The range in Generation 2 was from one to four explanations; the range in Generation 3 was from one to three explanations. This shift from none to low frequency occurred between Generation 1 and Generation 2. Because inferential statistics are not designed to compare a difference between zero and low frequency, this generational shift did not attain statistical significance. However, the increase of a feature from none to some is an important development in cultural evolution because cultural features adaptive in particular environments are selected for and become more frequent over time (cf. Fog, 1999). In addition, as our later analysis will show, it was part of the synergy with other Gesellschaft variables and was part of a successful three-generational model that integrated all three levels of analysis, sociodemographic change (the distal learning environment), teacher change (the proximal learning environment), and learner change.

Learner change across three generations

Hypothesis 13: Girls would have less weaving expertise in the current generation

We tested this hypothesis by examining the number of items girls had woven prior to the lesson we videotaped. Although the average age of the girls was approximately the same across the samples in the three generations, girls in Generation 3 had woven the fewest items prior to the weaving lesson we videotaped; means were one prior item in Generation 3 (to the closest whole number) vs. two in Generation 1 and Generation 2. An ANOVA confirmed that there was a significant intergenerational difference (F (2, 131) = 5.19, p = .007. partial eta squared = .073, medium effect size); the Games-Howell test confirmed that the only significant difference was the decline between Generation 2 and Generation 3 (p = .004). The range went from zero to five, the maximum, in each generation. Because learners gradually learn to weave more difficult items as they get older, we also carried out an analysis of covariance with age as the covariate and generation once again as the independent variable. This analysis confirmed that there were significant differences in the number of items girls had woven in the three generations (F (2, 130) = 4.30, p = .016, partial eta squared = .062, medium effect size). As expected, age was a significant covariate (F (1, 130) = 93.84, p < .001, partial eta squared = .42, large effect size).

Hypothesis 14: Schooling would compete with weaving; in other words, girls would not be learning to weave because they were attending school

This hypothesis was confirmed: Controlling for age, weaving expertise was negatively correlated with schooling. Those with more schooling had a lower level of weaving expertise, partial r (128) = −.24, p = .006, two-tailed test.

Hypothesis 15: Question asking, a trait adaptive in school, would increase across the generations

The frequency of girls asking questions was not high, but we found that the percentage of girls asking questions increased from Generations 1 and 2 to Generation 3: Percentage of girls who asked the teacher at least one question in each generation: In Generation 1, 14% of the girls asked questions; in Generation 2, 12% asked questions, and in Generation 3, 37% of the girls asked at least one question. We found that generation made a significant difference in question-asking: F (2, 131) = 6.39, p = .002, partial eta squared = .089, a medium effect size. The range was zero to one in Generation 1, zero to two in Generation 2, and zero to three in Generation 3. A Games-Howell test indicated that weaving learners in Generation 3 asked significantly more questions than learners in Generation 1 (p = .005) or Generation 2 (p = .004). Generations 1 and 2 are not significantly different from each other.

Hypothesis 16: Integrated model of changes in the distal learning environment, the proximal learning environment, and learner behavior

The data on which these results are based allow for comprehensive tests of the larger theoretical claim of this research—that changes in a community’s sociodemographic characteristics will lead to corresponding adaptations of learning environments which will in turn foster different developmental pathways. We begin with the correlations.

As an indicator of individual development adapted to a Gesellschaft ecology, we used the learner variable of the number of questions a girl asked during the first cycle of her weaving. The higher values of generation, distal learning environment, and proximal learning environment represent a Gesellschaft orientation, and number of questions was positively correlated with these variables (Table 4).

Table 4. Correlations among generation, distal learning environment, proximal learning enviornment, and learner variables.

	Generation	DIstal learning environment	Proximal learning environment
Distal learning environment	.72^****	–
Proximal learning environment	.25**	.28^****	–
Girls’ questions	.27**	.38^****	.55^****
Weaving expertise	−.21*	−.24**	−.25**

*p < .05; **p < .01; ***p < .001; ****p < .0001.

Note: Higher distal and proximal learning environment scores represent more Gesellschaft-adapted environments. Lower scores represent more Gemeinschaft-adapted environments.

As an indicator of individual development adapted to a Gemeinschaft ecology, we used the learner variable of weaving expertise - the ability to weave increasingly difficult items. The lower values of generation, distal learning environment, and proximal learning environment represent a Gemeinschaft orientation, and weaving expertise was negatively correlated with these variables (Table 4).

In sum, we created two causal models that would explicate the factors producing historical changes in learner skills. One model (Figure 2) identified factors leading to the intergenerational increase in question-asking while learning to weave, a transformation of cultural transmission in the Gesellschaft direction. The other model (Figure 3) identified factors leading to the intergenerational loss of weaving expertise, a key skill that was required and adaptive in the subsistence Gemeinschaft ecology of Nabenchauk in earlier times.

Figure 2. Test of the indirect effect of generation on the number of girls’ questions as mediated by the sequence of the effect of the distal learning environment on the number of girls’ questions through learning environment.

Note: Significant positive coefficients indicate that the younger the generation, the more the social ecology was Gesellschaft-adapted as indicated by the sociodemographic characteristics in the distal learning environment (a₁), and the more Gesellschaft-adapted the sociodemographic characteristics in the distal learning environment (b₁) and proximal learning environment (b₂), the more questions the girls asked. That the direct effect (c‘) is not significant means that the correlation between generation and girls’ questions is largely explained by the sociodemographic characteristics comprising the distal learning environment (a₁ b₁: CI = [.044, .641]) and the serial mediation of the distal learning environment through the proximal learning environment (a₁ d₂₁ b₂: CI = [.005, .295]).

⁺p < .068; *p < .05; ****p < .0001.

Figure 3. Test of the indirect effect of generation on weaving increasingly difficult items as mediated by the sequence of the effect of the distal learning environment on the ability to weave through the proximal learning environment.

Note: The significant positive coefficients indicate that the younger the generation, the more the social ecology was Gesellschaft-adapted, as indicated by the sociodemographic characteristics (a₁). The significant negative coefficient indicates that the more Gesellschaft-adapted the proximal learning environment, the fewer difficult pieces were woven by the girls (b₂). That the direct effect (c‘) is not significant means that the correlation in which younger generations were less likely to weave difficult pieces is largely explained by the serial mediation of the distal learning environment through the proximal learning environment (a₁ d₂₁ b₂: CI = [-.212, -.012]).

⁺p = .065; *p < .05; ****p < .0001.

Tests of serial mediation (Hayes, 2018) allow testing the predicted models that differences between the generations of weaving learners in the number of questions they asked in the learning session and differences in weaving expertise might be explained by differences in sociodemographic characteristics of the distal learning environment and features of the proximal learning environment during weaving. Importantly, in the predicted models sociodemographic characteristics of the distal learning environment followed by proximal learning environment should be the effective mediators between generation and girls’ questions.

The test of the whole model in Figure 2, with girls’ questions as the dependent variable and generation, distal learning environment, and proximal learning environment as predictor variables without considering specific paths of mediation, is significant (F(3,130) = 24.04, p < .0001.) Figure 2 shows the tests of the potential paths of mediation. As expected and illustrated in the figure, there was no direct effect (c‘) of generation on girls’ questions. Also as expected, generation does predict distal learning environment (a₁). When taking generation into account, both distal learning environment (b₁) and proximal learning environment (b₂) predict girls’ questions.

The tests for mediation entail combinations of these paths. In terms of the critical test of the total theoretical model, there is serial mediation (a₁ d₂₁ b₂: CI = [.001, .262]) such that there is an indirect effect of generation on girls’ questions through the serial mediation of distal learning environment followed by the proximal learning environment. These results confirm the predicted model in which each generation is proposed to have a different distal learning environment with distinct sociodemographic features; each distal learning environment then produces a different proximal learning environment - i.e., teacher-learner interaction while learning to weave. Finally, these differences in proximal learning environment then predict different pathways of children’s behavioral development as learners, which in this case is whether or not girls will tend to ask questions of the teacher during a weaving lesson.

The test of the whole model in Figure 3, with weaving expertise as the dependent variable and generation, distal learning environment, and proximal learning environment as predictor variables, without considering specific paths of mediation, is statistically significant (F (3,130) = 4.38, p < .01.) Figure 3 shows the tests of the potential paths of mediation. As with the previous model and as expected, generation does predict distal learning environment: participants from each subsequent generation are from smaller families, participate in more commercial activity; and receive more schooling; in Generation 3, participants also have mobile technology (a₁). When taking generation into account, a more Gemeinschaft-adapted distal learning environment (larger families, less commercial involvement, less school experience of both learner and mother, and less mobile technology) and a more Gemeinschaft adapted proximal learning environment, (less teacher explanation, less praise, and less body instruction during the weaving lesson) does predict greater weaving expertise (b₂).

The tests for mediation entail combinations of these paths. In terms of the critical test of the total theoretical model, there is serial mediation (a₁ d₂₁ b₂: CI = [-.201, –.003]) such that there is an indirect effect of generation on weaving expertise through the serial mediation of distal learning environment followed by proximal learning environment.

These results confirm the predicted models in which each generation is proposed to have a different distal learning environment with distinct sociodemographic features; the distal learning environment typical of a Gesellschaft ecology then produces processes of weaving apprenticeship - learning environment and child behavior - adapted to this ecology; but these Gesellschaft-influenced processes also lead to a decrement in weaving expertise.

Discussion

In this age of globalization, where cultural groups are experiencing rapid changes in economics, demographics, and daily routines, we aimed to study links between macro-level shifts and micro-level learning interactions. Using the Zinacantec Maya community of Nabenchauk in Chiapas, Mexico, as a natural laboratory, we found coordinated changes over a period of more than 60 years in the distal learning environment on the macro-level and the proximal learning environment and learner behavior on the micro-level of weaving apprenticeship. Commercial activity and education expanded for both learners and teachers, mobile technologies began to be used, and family size decreased—all features of the distal learning environment. As these ecological shifts occurred, the proximal features of intergenerational cultural transmission also changed: weaving teachers praised and explained more while criticizing less, and they responded to learners’ increased needs for bodily instruction by providing it. In turn, these historical shifts produced an increase in question-asking while learning to weave, a Gesellschaft-adapted skill valued in an educationally oriented society, and a decrease in weaving expertise, a Gemeinschaft-adapted skill valued in a subsistence-oriented community.

Fewer girls were learning to weave in 2012 because they were involved in other kinds of activities, including attending school, producing on order (for pay) specialized aspects of textile creation (e.g., drawing patterns for fancy embroidery), or working with their families in other kinds of commerce (Greenfield, 2004; Greenfield et al., 2009). Because many girls were not learning to weave, the number of items girls had woven prior to our videotaped weaving lesson had decreased significantly by 2012, controlling for learners’ ages. This was the case even though the average age of the girls was approximately the same across the three generations. The decline of weaving expertise is a major phenomenon of Maya cultural evolution; this is the case because backstrap loom weaving has been the most complex technology of Maya culture that has survived over the millennia.

Schooling competed with weaving. This finding demonstrates, on the level of individuals in a defined sample, the general anthropological conclusion that school attendance pulls children away from learning subsistence skills (Lancy, 2012). Even more interesting in terms of learning processes, girls who had more schooling behaved differently in the weaving lesson than those with less schooling. Specifically, weaving learners who had been to school asked more questions as they wove in front of the video camera.

Our integrated model showed that girls whose mothers had been to school also asked more questions. Asking questions is a form of self-assertion, a quality that is adaptive in a Gesellschaft ecology. Asking questions is, moreover, something that teachers do; and children are encouraged to do the same in school. Prior research has shown that going to school leads children to internalize the role of the teacher (Maynard, 2002), a role that includes question-asking. An important point is that the practice of asking questions in the context of formal education carried over and generalized to weaving apprenticeship, a process of informal education. In sum, as the evolution of community culture made backstrap-loom weaving less central, intergenerational transmission also evolved, reflecting cultural features that were gaining importance over time—most notably schooling.

The topic of socialization in developmental psychology does not generally include the socialization of the physical body and bodily movements. Yet weaving is both a bodily skill and a cognitive skill (Maynard et al., 1999; Greenfield et al., 2003; Maynard et al., 2015). Therefore, the use of the body was of great interest to us. Compared with Generations 1 and 2, girls in Generation 3 required more instruction in how to use their bodies in weaving. This is because kneeling, a long-established proper body position for Zinacantec Maya females, had diminished in favor of sitting in chairs, at home and at school (for those who went to school). We believe that the everyday use of chairs and the decrease in girls’ weaving experience are factors in the need for body instruction. Our case study of AE showed that body position could not be taken for granted by girls who went to school and had no experience in everyday life of kneeling to carry out various activities.

We have traced how the shift at the ecological level from Gemeinschaft to Gesellschaft engendered intergenerational changes in the learning environment, in turn shifting learner behavior in each generation. This cross-cohort comparative design has demonstrated how cultural evolution can be directly observed and assessed on multiple levels across multiple generations. Our findings provide an empirical demonstration of nested levels of environmental influence very much in the spirit of Bronfenbrenner’s (1977) Ecological Systems Theory.

But our research also documents that these multilevel changes come at a cultural cost - the gradual loss of weaving as an everyday subsistence practice and art form. In this too, the village is a microcosm of Mexico and the globalizing world.

Broader implications

These shifts in the macro-environment in the Gesellschaft direction are happening on a global level. Many societies and communities beyond our study site have moved in recent generations from agriculture and subsistence lifestyles to commerce, formal education, and technology (e.g., Abu Aleon et al., 2019; Weinstock et al., 2015; Zeng & Greenfield, 2015). In addition, migrants all over the world are moving from communities based on agricultural and subsistence lifestyles to host societies that have highly developed commercial, educational, and technological ecologies (e.g., Greenfield et al., 2019). Therefore, our longitudinal findings in Nabenchauk are applicable to shifts in learning environment and cognitive development brought about by endogenous social change and migration all over the world. The traditional view in developmental psychology that cultural differences are static does not take into account the fact that the influences on learning undergo massive change over time, making learning and cognitive development dynamic processes, and producing altered patterns of cognitive development (Maynard et al., 2015; Weinstock, 2015).

As Zinacantec girls over time asked more questions as they and their mothers were exposed to more formal education, their behavior became more like the children teachers expect to teach in the U.S. or Western Europe. This finding illustrates another broader implication of the present research: the global direction of social change in the Gesellschaft direction often has the effect of reducing cultural differences in child development (e.g., Zhou et al., 2018).

However, lest we mistakenly view the emerging patterns of development as progress, we need to remember the cultural losses from movement away from a Gemeinschaft ecology. On the physical level, we have documented loss of the ability to kneel as the human-made environment has changed. In Chiapas, Mexico, weaving as a cultural practice is a loss in Maya communities across the state resulting from the increase in educational opportunity (Zambrano, 2000). Such losses are also applicable to communities in other countries moving from subsistence life styles to life in Gesellschaft environments. For example, with immigration to Israel, Ethiopian immigrants now value formal education and technology, but devalue their artistic practice of clay sculpture, originally a subsistence practice in their ancestral country of Ethiopia (Greenfield et al., 2019). While we need to understand that there are developmental losses as well as gains from ecological movement in the Gesellschaft direction, we also need to remember that each set of cultural practices is adapted to a different set of ecological circumstances.

Limitations

It would be interesting to know if delayed childbearing was a factor in producing smaller families. Because we have not calculated each mother’s age when she bore her first child, we do not know if this was a factor in family size. We will be able to assess this factor in the future. Undoubtedly, some mothers continued to have children after the study; and these could not be counted in our assessment of family size. This is a limitation on our accuracy in reporting family size, but it is a constant across the generations, so does not affect our statistical comparison across the three generations.

Another limitation of the present study is that the coders of the videos were not blind to all hypotheses, particularly because we had published articles together based on the first and second generations. However, the coding system was rather rigid (how many seconds of this, what grammatical structure of that sentence, positive or negative statements). It would be hard to alter the coding systematically to fit a hypothesis. Furthermore, we achieved strong to perfect reliability on the coding of a random set of videos, which also adds to credibility. It would have been impossible to find coders who could weave, speak Tzotzil, and had enough formal education to understand the coding process in order to achieve blind coding.

Educational application and implications for cognitive development

Children’s questions have commonly been seen as a part of cognitive development that is essential to learning in formal and informal learning environments (Chouinard et al., 2007; Haber et al., 2021). Inquiry-based learning, which, as the name implies, centers on raising questions, specifically from learners, is often seen as the gold-standard of educational practice (Geier et al., 2008; Nicolopoulou et al., 2021). However, much educational practice and developmental research treats children’s question-asking and the types of questions they tend to ask as if it were a natural process rather than the product of adaptation to different learning environments. Many educators give a nod to sociocultural practices, seeing schooling and instructional methods as sociocultural practices, but still expecting that children naturally ask questions in the way they, the educators, do. Our research indicates that children’s questionasking is not natural but culturally specific, an adaptation to the learning environments and cognitive development of Gesellschaft social ecologies (Jegede & Olajide, 1995). The current research indeed found that the latest generation of weavers asked more questions of their teachers in the course of learning, which, we argue, is indicative of the change in the social ecology from the earlier generations toward more Gesellschaft-adapted learning environments and a subsequent shift toward Gesellschaft-adapted cognitive development.

These findings are very applicable for teachers. Many children in the United States and Europe come from immigrant families in which parents are from rural more Gemeinschaft environments than the environment of their host country. In such communities, questions can be considered a mark of disrespect; agricultural workers in California from Mexico or Central America provide an example of this cultural interpretation (Delgado-Gaitan, 1994). Children from such environments are socialized to show respect to parents and teachers by NOT asking questions.

What teachers can take away from this analysis and our findings is that children brought up in this way may not engage in the question-asking valued in school. When children have experienced this type of cultural socialization, teachers can learn from our research to treat the absence of children’s questions as a cultural trait rather than a cognitive deficit. However, because questions are valued in the host culture, teachers can also be explicit about the difference between home and school cultures and, early in their education, gently guide children toward the question-asking so important and valued in formal education.

In addition to environmental influences on the presence vs. absence of learner questions, there are also ecological factors in the types of questions that are relevant and valued. Much of the research regarding children’s questions, at least with U.S. samples, highlights different types of questions than the ones the most recent generation of weaving learners were asking. For instance, Chouinard et al. (2007) report that preschool children’s questions tend to be fact or causal explanation seeking. The Zinacantec weaving learners' questions concerned learning the procedure. We argue that the differences in the types of questions students ask in the weaving environment or in formal schooling are not just a matter of age difference, but also reflect the different goals of the two learning environments. So, children in school might not be asking about procedures, because theoretical knowledge and not procedures are the center of schooling; insofar as procedures are involved—such as in science class labs—these are not done for their own sake but in the service of theoretical learning. This contrasts with the tasks of teaching and learning to weave. But that different types of environment entail very different tasks is precisely the point. Teaching and learning, and children’s cognitive developmental tasks are adapted to the learning environment.

Direct application to classroom teaching is also possible. Author Childs, who teaches sixth graders in the U.S., has applied our research in a very concrete way to teach about cultural relativity, more specifically, to teach students that children are taught differently in different ecological circumstances. She sets up a backstrap loom in a classroom, demonstrates how weaving is done, and then asks a student to get into the loom. She then provides a demonstration of teaching as it was done in our first generation of weaving learners: criticism rather than praise; imperatives rather than questions; observation rather than doing; replication rather than innovation. She also explains that in such an environment, education takes place primarily at home rather than at school. She points out that these are teaching and learning procedures they have probably never even imagined exist. While many of the students find Childs' demonstration quite alien, a number of them come to understand something about profound cultural differences; hence the demonstration functions as a lesson in cultural relativity.

Childs also points out to her students that, as Zinacantec Maya environments have become more like ours, most recently with increased opportunities for formal education, teaching and learning procedures have also become more like ours. She uses her example of backstrap-loom weaving in Nabenchauk to teach that modes of teaching and learning are adapted to particular environments and that they therefore change as environments shift over time. This innovative application of the research is a concrete, valuable example of using it in an educational setting.

Acknowledgements

Our third wave of data collection (2012) was supported by grants from the Spencer Foundation, UC MEXUS, and the UCLA Latin American Institute. The UCLA Center for the Study of Women provided financial administration. Grateful thanks to our field assistant, Maruch Ch’entik, who also assisted with the second wave of data collection in 1991. Finally, we thank our study participants in Nabenchauk, many of whom are the third generation of their families to participate in our studies.

Data availability statement

The data that support the findings of this study are available from the corresponding author, Ashley Maynard, upon reasonable request.

Disclosure statement

No potential conflict of interest was reported by the authors.