Miles’ law in Finnish municipalities: where decision-makers stand depends on where they sit

ABSTRACT

Miles’ Law, i.e., the notion that institutional position affects attitudes, is considered a truism, but not much attention has been given to properly test or develop it. Here, we argue that Miles’ Law is effective not only for civil servants but among municipal decision-makers in different positions. We examine how well institutional position can explain differences in attitudes to welfare service provision among decision-makers on different levels. Differences in opinion depending on institutional position are usually overlooked when attitudes on welfare are explained. Using survey data (N = 1,578) from 42 municipalities in Finland, our analyses show that institutional position does affect attitudes to service provision. However, the differences are contingent on the mode of service provision under consideration and are moderated by the size of the municipality and the economic status. This shows that it is important to consider the position of local government decision-makers to understand their attitudes.

KEYWORDS:

• Attitudes
• Miles’ law
• Finland
• municipalities
• service provision
• decision-makers

Introduction

Miles’ Law asserts that the institutional position of civil servants affects their attitudes (Miles 1978). This idea is epitomised in the phrase principle ’where you stand depends on where you sit’ (Miles 1978, 399). The idea is that rather than being neutral servants, the judgements and interests of civil servants are very much influenced by organisational affinities.

Although Miles formed his law studying the behaviour of civil servants, we here build on a similar line of reasoning and examine the extent to which municipal decision-makers, including elected politicians, are affected by the perspective given by their institutional position in the municipal hierarchy. According to this line of reasoning, decision-makers are influenced by their position since their knowledge and experiences vary depending on what offices they hold, which according to Miles’ Law is supposed to influence their attitudes.

Whereas civil servants are expected to be neutral in carrying out their duties, elected decision-makers are expected to be primarily influenced by party affiliation or ideological affiliation. Nevertheless, for both groups, their actions may also be guided by other factors, such as their role in the organisation where they perform their duties. Earlier studies have indicated that position may affect attitudes for politicians and officials (Pierre et al. 2017; Røiseland 2016; Walker et al. 2011; Wildavsky and Caiden 2001; Olsen 1970). Other studies show differences in opinions between politicians at different levels in the municipality (see Sandberg 2012; Pikkala 2005, 1997, 166; Olsen 1970; Heinelt 2013). Nevertheless, there is still no overarching study of how positions may affect attitudes of local decision-makers.

We here contribute to this research agenda by examining the effects of institutional position on attitudes towards service provision in Finnish municipalities. Furthermore, we examine the extent to which these associations are contextually dependent by examining the moderating effects of two key contextual factors, namely municipal size and economic situation. The data come from a survey from 2015 administered to decision-makers in 42 Finnish municipalities (n = 1578).

We focus on attitudes towards service provision since this is a central responsibility for Finnish municipalities, as a large share of the welfare services in Finland are produced by municipalities. Although the overall terms are settled nationally, municipalities have a broad leeway in deciding on how the provision of services should be organised. This entails that we are likely to observe variation in the attitude towards service provisions. As part of the analyses, we identify attitudes to different modes of service provision to acknowledge that welfare service is a multidimensional phenomenon. Since the role of parties is less emphasised, Finland constitutes a most-likely case for examining whether Miles’ Law can help understand differences in attitudes among local decision-makers.

The results from several multilevel logistic regression models suggest that the effect of position on welfare service attitudes is significant, but also dependent on the mode of service under consideration. We also find that municipal size and the economic status moderate the relationship. All of this shows that Miles’ Law does not only affect civil servants, but plays a role in understanding the attitudes of a broader set of municipal decision-makers.

This article proceeds as follows. First, we present core assumptions and earlier research on Miles’ Law and explain why it is reasonable that the position affects opinions on welfare service provision also in the case of local decision-makers. Second, we discuss how the Nordic welfare tradition and the Finnish electoral system make this especially relevant in Finnish municipalities. We then move on to present data and variables before moving on to the empirical analyses of the associations between position on welfare attitudes. We conclude with a discussion of what our findings entail.

Concepts and theory: on the genesis of attitudes towards welfare service provision

Institutional position or where you stand depends on where you sit

Miles´ Law, named after Rufus E. Miles Jr., embraces the idea that attitudes are formed by the position an individual serves in. Miles was a ‘distinguished federal administrator who served in numerous high-level jobs’ (Stillman 1999, 92; Machol 1978, 86). During his work as chief at the Bureau of the Budget (of the United States) in the late 1940s, he articulated the principle ’where you stand depends on where you sit’¹ (Miles 1978, 399). This principle was used to explain how one of the most arduous examiners of the Bureau, after changing agency reversed his opinions fundamentally in favour of the perspective of the new agency and against the Bureau (ibid.). The behaviour is explained by new responsibilities, expectations and roles that came along with the new position (Stillman 1999, 92). Miles’ Law entails that individual attitudes and interests are not only determined by predispositions such as ideological affinities and personality, but also depend on the organisational environment where the individual operates (Miles 1978, 399).

Although Miles spells out that ‘the more conscious one becomes of its operation, the more frequently its effects are noticed’ (Miles 1978, 400) there is not a widespread use of this notion in the research on public opinion or social sciences in general. Studies ‘either ignore Miles’ Law … ’ (Berman, Martin, and Kajfez 1985), do not offer testable propositions (Marsh and Jones 2017, 544) or build on case studies. In the field of foreign policy, however, the notion of Miles’ Law is used as an integral part of the bureaucratic politics model of foreign policy decision-making (Marsh and Jones 2017; Allison 1969; Allison and Halperin 1972). Scholars using Miles’ Law usually find support for the proposition (Berman, Martin, and Kajfez 1985; Buckley and Tucker 2019; Chen 2012; Pedersen, Pedersen, and Bhatti 2018; Jae-Won and Wright 1994).

However, although Miles’ original work focused on employed officials, it is possible that the law has wider implications. According to Miles, ‘[e]very person has a function to perform and that assigned responsibility markedly influences one’s judgement’ (Miles 1978, 400). Hence, there is no a priori reason to expect this logic to be restricted to the administrative part of the political system. Although Miles made his claim about administrators, he never stated that the mechanism works exclusively for public administrators.

For this reason, we here examine whether Miles’ Law also applies to decision-makers in Finnish municipalities. Where this to be the case, it entails that we need a deeper understanding of how the attitudes and behaviour of top-level decision-makers are shaped by how they are embedded in the political system, rather than only considering their individual characteristics and/or party affiliations that are often predominant. We use the term local decision-makers to clarify that we study elected politicians as well as top-level administrators of which some, but not all, are selected based on party affiliation (Haveri, Airaksinen, and Paananen 2015).

There are valid reasons to expect Miles’ Law to have some bearing on local level decision-makers as well. Although they do not form part of the municipal administration, they work in close cooperation with the administrative personnel connected to their position, on different levels in the municipality. This close cooperation may well shape their perspective as much as or more than their party affiliation, since the same issue can be perceived differently in different positions, on different levels. The interaction with other people may give them new perspectives that differ from the party-political orthodoxy and thereby entail that their attitudes are shaped more by their organisational commitments.

Contrary to conventional wisdom, decisions do not always reflect ideological party politics in the daily politics of service provision since many matters within the local administration do not have a clear ideological basis. For example, a politician may ideologically prefer increased privatisation of welfare services due to a belief in the superiority of the free market, but this may not be a viable option in a small rural municipality where there are no actors on the private market who would be willing or able to provide services at a reasonable price. Therefore, the decisions on service provision are seldom made only based on ideology.

Differences is attitudes in different political positions have been shown in Finnish municipalities (e.g., Pikkala 1997; Sandberg 1997; Ståhlberg 1997; Pikkala 2005; Sandberg 2012, 88). The effect of position as an independent explanation has, however, been noticed only sparsely in the literature on local government, with the exception for the work by Pedersen, Pedersen, and Bhatti (2018). Usually, position or earlier experience from different positions are mentioned as things that matters in passing, without explicating how (e.g., Vabo 2000, 366, Bowman 2017).

Including the lessons from Miles’ Law can help explain intra-party conflicts between politicians from different sectors and different levels of the decision-making system. Based on Miles’ Law, we in our first hypothesis posit that decision-makers’ positions should have a bearing on their attitudes to service provision.

H1:

The position of decision-makers in the local administration affects their attitudes.

Attitudes by size and economic pressure

How exactly the positions shape attitudes is likely to be dependent on the context, in this case the characteristics of the municipalities where the decision-makers operate. It may well be that the position is particularly likely to affect key attitudes under certain preconditions that make the position relevant, while it may otherwise be largely irrelevant. We here focus on two contextual factors that are particularly likely to be relevant moderators in a Finnish context.

The relations between the size of the local government and its effects concerning functional effectiveness and democracy are always present (since Dahl and Tufte 1973; Newton 1984 and further). Here, the question of size is quite intimately connected to the question of centre and periphery (Rokkan 1999; Stein, Buck, and Bjørnå 2019), i.e., urban versus rural municipalities, because the size and the location of the municipality very heavily affects its service provision, due to tax bases and distances (Giritli Nygren and Nyhlén 2017, 340). The less inhabitants in the municipality, the more vulnerable service provision and the more there is to lose. In polycentric municipalities with large distances (Hirvonen, Karhila, and Saukkonen 2016, 5–6) there may be tensions also within the municipalities, affecting the attitudes of different actors. Further, municipal size also affects the size of the government and hence both decision-making scope and party politics. All of this entails that the size of the municipality is likely to affect when positions affect attitudes to service provision.

The second potential moderator that we examine is the state of the economy in the municipality. There are large socio-economic differences across Finnish municipalities in their preconditions for delivering services. While some experience economic prosperity, others struggle with providing basic welfare services (André and García 2014). These differences are likely to have consequences for how relevant positions are for attitudes to service provision. As Fredriksson et al. (2010, 639) states, ’attitudes among decision makers could be influenced by the economic situation of their municipalities’. Expectations of cost benefits have shown to be the most crucial factor in explaining willingness to increase the use of contracting out (Fredriksson et al. 2010) and other service-related reforms (Haveri 2015). Our third and final hypothesis therefore concerns how the economic situation of the municipality moderates the impact of position on attitudes.

H2:

The population size of the municipality moderates the associations between decision-makers’ position in the municipality and attitudes.

H3:

The economic situation of the municipality moderates the associations between decision-makers’ position in the municipality and attitudes.

In the following, we introduce the case of Finland and the question of service provision, which is the matter that we focus on when examining our hypotheses.

Finnish municipalities and welfare service provision

We examine our hypotheses in Finland by studying how decision-makers’ positions in the municipal organisation affect their attitudes to service provision. In the following, we first explain why the Finnish municipal system provides a possibility for examining the impact of Miles’ Law, before justifying our focus on service provision for examining this impact.

In this article, position refers to status in the Finnish municipal system. Local decision-makers fall into three categories. The council members are elected representatives of the council, while board members are members of the executive board, which is appointed by the council. The members of committees for different policy areas are also appointed by the council. Members of the board are usually (but not always) also members of the council, while committees are populated by both council members and other party members (mostly candidates in elections that were not elected). We contrast these three categories of politicians against the senior civil servants, including the municipal CEO, who are professional leading public officials (leading officials) in the municipality (but not elected or politically appointed), bearing responsibility for the municipal departments. They are not politicians but do count as municipal decision-makers, since their authority is broad (following the council-manager form of power relations, by Mouritzen and Svara 2002, 56) and political (although not party-political), because Finnish municipal politicians (with a few exceptions) are layman. The second reason for including them is that most (although not all) of the officials are accountable to the council (in the same manner as the executive board and the committees).

These different positions entail that decision-makers experience different cues from their political undertakings, with different responsibilities, expectations and roles that came along (see Stillman 1999, 92) with the mandate. While some handle issues concerning the entire municipality, other are submerged in committees working with specific policy areas. This is likely to affect how they perceive different issues maybe even more than party affiliation.

The Finnish electoral system is an open-list proportional representation system (Karvonen 2010). Since voters cast their vote for a candidate rather than a party list, the system is highly candidate-centred (Söderlund 2020). At the same time, municipal decision-making in Finland has a consensual nature, where boards and committees are appointed following the principle of proportionality and the lack of a government-opposition divide decreases ideological competition (Fredriksson et al. 2010, 651). Miles’ Law may be especially relevant in this context, where political parties have no easy way to control the composition of the assembly.

Our focus on service provision is motivated by the central role welfare services has for the municipalities in Finland. Finland follows a Nordic tradition of extensive service provision (Haveri 2015; see also Sellers, Lidström, and Bae 2020) which has traditionally consisted of public responsibility, public funding and public service provision (Lundqvist 1988). An exceptionally large share of welfare services in Finland has been provided at the municipal level (Haveri 2015; Anttiroiko and Valkama 2017, 153; Moisio and Uusitalo 2013, 151). This entails that while the general terms are decided at the national level, local decision-makers have a broad leeway when deciding on how issues such as healthcare, care of the elderly ,² schools and day-care are organised on a daily basis. For example, local decision-makers decide whether the municipality produces services independently, in cooperation with neighbouring municipalities, or contract out the service provision to private actors.

Finland has relatively small municipalities.³ The ambitious welfare service responsibilities (Haveri 2015, 141, Fredriksson et al. 2010, 638) entails that most municipalities cannot carry the burden independently (Fina et al. 2021, 13–15). A number of reforms have since the 1990s aimed to improve or streamline service provision in Finnish municipalities (Haveri 2015; Nygård 2006). These reforms include various options, such as cut-backs by reducing the number of service points, digital solutions, and increasing the use of contracting out. A particularly salient issue has been the extent to which services should be produced by public or private providers (Fredriksson et al. 2010; Nygård 2006).

These reform efforts have ensured that service provision has remained top of the political agenda in most municipalities. For the present purposes, it is worth noting that studies of the factors explaining differences in service provision in Finnish municipalities show that ideology may explainattitudes to service provision, but not the use of private service providers (Fredriksson et al. 2010; Granqvist 1997). This shows that there is a need to include other factors to explain attitudes to service provision.

Svallfors (2011) argues that attitudes to welfare is a multidimensional concept comprising dimensions such as trust in welfare achievements, funding, and organisation. We here follow this multidimensional approach and take into account the fact that attitudes towards welfare service provision are not uniform, but likely to be structured along separate dimensions.

Materials and methods

The data is based on a survey carried out in 2015 in connection with a research programme named ARTTU2 (for description, see Meklin et al. 2020). The survey was sent (by webropol/email) to all regular members of the municipal council, the municipal executive board, the municipal committees as well as to the leading officials (the CEO, the branch managers and other central officials). This survey was sent to 3,652 persons in 42 municipalities and answered by 1,578 (43.2%) although some respondents are excluded from analyses due to missing values. The data set was combined with register-based public data on municipal size and finances from the 42 municipalities, who were of different types and sizes located in different parts of Finland and constitute a representative sample of Finnish local authorities.

Variables

Our dependent variable concerns attitudes to service provision, which we operationalise with a battery of 10 statements on service provision in the municipality: Many municipalities are reforming their service. How important are the following matters in your municipality? answers on Likert scale 1–5 (1 not at all important, 5 = very important). These questions make it possible to probe how the respondents feel about key aspects of service provision in their municipality. While there is a potential risk that the answers are guided by the situation of the municipality rather than individual perceptions on service provisions, this risk is minimised by the low intra-municipal variance that we observe.⁴

Following the multidimensional approach to attitudes, we examine the underlying dimensionality with exploratory factor analysis (principal component factoring with promax rotation). All dimensions with an eigenvalue over 1 were extracted but confirmed the results with a parallel analysis that suggested a similar number of dimensions, see Table 1.

Table 1. Factor analysis of 10 statements on service provision.

Variable	1	2	3
Services remain to be provided by the municipality	−.386	.226	.633
Services provided as close as possible to home	.136	−.222	.813
Flexible use of services in the neighbouring municipality possible	.565	.012	.503
Flexible use of services offered by associations and companies possible	.822	.027	.209
High quality service guaranteed, even if the number of service points are reduced	.042	.719	−.226
Flexible use of use digital services possible	.136	.681	.128
More ambulatory services, even if the number of service points are reduced	.-.020	.787	−.047
Publicly funded consumer choice between public and private service providers (vouchers)	.789	−.013	−.148
Greater own responsibility for own health and welfare	.599	.214	−.049
User and service fees to be introduced and/or increased	.605	.034	−.273
Eigenvalue	3.265	1.517	1.156

Note: The entries are results from a factor analysis (Principal component factoring) with promax rotation and all dimensions with eigenvalues over 1 extracted. Loadings between .5 and .6 are shaded in light grey and loadings >0.6 are shaded with dark grey. Eigenvalue of the fourth factor not extracted: 0.903. Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO) = .768; Bartlett test of sphericity (df = 45): Χ² = 3452.79, p < .001.

The results indicate three underlying latent dimensions of service provision. The first dimension concerns the importance of Individualisation in service provision, meaning that the items loading on this dimension aim to ensure greater flexibility for the individual citizen, mostly by vouchers to enable a greater share of private service-providers. The second dimension concerns Centralisation in service provision since it includes items emphasising provision of high-quality service by centralising the supply of services. Finally, the third dimension concerns localised public service provision, since it includes items that concern public provision of services in the local municipality. The first two dimensions bear obvious traces of New Public Management and the centre-perifery divide, which make them interesting for two reasons. First, they are both ideologically coloured, although from different perspectives. While individualisation may speak differently to people from different parties, centralisation may speak differently to people from municipalities of different size. Hence, the last dimension is different. Most people like services close to home. This conceptualisation also resembles the one used by Nygård (2006), and we use these three dimensions as dependent variables in our empirical analyses. They are measured by predicting the values of each dimension using the regression score method and the variables are standardised to have a mean score of 0 and a standard deviation of 1.

The main independent variable is a categorical variable indicating the position of the respondent. The Leading officials (n = 214, 13.6%) are employed by the municipality. The politicians are divided into three groups according to the position perceived as most influential: Board members (n = 355, 22.5%), Council members (n = 608, 38.6%) or Committee members (n = 398, 25.3%).⁵

We rely on two contextual variables to examine differences across contexts: municipal population size and economic situation. Municipal population size is coded as a categorical variable with three categories dividing municipalities into small (less than 20,000 inhabitants), intermediate (20,000–100,000 inhabitants) and large (more than 100,000 inhabitants). While it may seem unusual to consider municipalities with more than 100,000 inhabitants as large, this is reasonable in a Finnish context, where most municipalities have few inhabitants and only nine municipalities have more than 100,000 inhabitants.

For economic status, we rely on an official classification of economic pressure that categorises the economic situation of municipalities based on several economic indicators such as yearly deficits, and local income tax rate, as decided in § 118 of the Finnish Municipal Act (410/2015). This classification is used to catch municipalities that are economically unable to live up to their service obligations, and therefore has direct consequences for the economic freedom of the municipality. This variable is an ordinal variable with five categories coded to vary between 0 and 1, where a higher score indicates a higher state of economic pressure.

We include control variables at the individual level to ascertain that the differences observed are due to position rather than other factors, but restrict our selection to basic socio-demographic characteristics that are unlikely to be affected by what position people hold in the municipality. These include education, gender, and whether employed in the private sector since these are all basic characteristics that have been shown to affect attitudes towards welfare service provision (Blekesaune 2007; Lipsmeyer and Nordstrom 2003). We also include party affiliation, which is particularly important for our purposes since it juxtaposes the position with ideological commitments, which may otherwise be expected to be a primary explanation for attitudes on service provision in accordance with the theoretical arguments above.

Table 2 shows summary statistics for all variables.

Table 2. Summary statistics.

	Obs	Mean/%	Std. Dev.	Min	Max
Dependent variables
Individualization	1470	0.00	1.00	−3.82	2.17
Centralization	1470	0.00	1.00	−3.73	2.24
Localization	1470	0.00	1.00	−3.15	2.46
Independent variable
Position	1575	100.00
Leading official	214	13.59
Board member	355	22.54
Council member	608	38.60
Committee member	398	25.27
Contextual variables
Municipal population size	1575	100.00
Small (<20,000)	310	19.68
Medium (20,000–100,000)	860	54.60
Large (>100,000)	405	25.71
Economic crisis status	1575	0.32	0.17	0.00	0.75
Control variables
Education	1565	0.67	0.33	0.00	1.00
Gender	1549	100.00
Female	670	43.25
Male	879	56.75
Private employment	1575	100.00
No	1093	69.40
Yes	482	30.60
Party affiliation	1501	100.00
Don’t want to say/no answer	211	14.06
National Coalition Party (KOK)	252	16.79
Christian Democrats (KD)	44	2.93
Finns Party (PS)	131	8.73
Swedish Peoples Party (RKP)	128	8.53
Center Party (KESK)	261	17.39
Social Democrats (SD)	286	19.05
Left Alliance (LEFT)	91	6.06
Green Party (GREEN)	97	6.46

Note: Entries are descriptive statistics for continuous and categorical variables.

We examine the relationship using multilevel modelling to take into account that our 1578 respondents are nested into 42 municipalities (Gelman and Hill 2007; Hox 2010). We examine the moderating effects of municipal characteristics by including interaction terms between the position variable and the two contextual variables municipal population size and economic status (Kam and Franzese 2009). Results of the regression analyses are presented visually for ease of interpretation, but all models are included in the appendix.

Results

We first examine differences in mean scores on the three dimensions of service provision depending on position, as reported in Table 3.

Table 3. Mean scores on service provision dimensions.

Individualisation		(1) Leading officials	(2) Board member	(3) Council member	(4) Committeemember
Mean (SD)		0.42 (0.80)	0.09 (0.96)	−0.07 (1.03)	−0.21 (1.01)
ANOVA F(3, 1466)=		19.86, p < 0.001
Bonferroni	2	−0.33**
	3	−0.49***	−0.16
	4	−0.63***	−0.30***	−0.14
Centralisation		(1) Leading officials	(2) Board member	(3) Council member	(4) Committeemember
Mean (SD)		0.58(0.86)	−0.01(1.00)	−0.06(0.97)	−0.21(1.01)
ANOVA F(3, 1466))=		30.23, p < 0.000
Bonferroni	2	−0.59***
	3	−0.64***	−0.06
	4	−0.79***	−0.20*	−0.15
Localisation		(1) Leading officials	(2) Board member	(3) Council member	(4) Committeemember
Mean (SD)		−0.47(0.96)	0.03(0.96)	0.05(1.00)	0.15(0.99)
ANOVA F(3, 1466)=		18.32, p < 0.000
Bonferroni	2	0.50***
	3	0.52***	0.02
	4	0.61***	0.11	0.10

Note: Entries are mean values with standard deviations in parentheses. Statistical tests are oneway Anova with Bonferroni post hoc tests. *** p < .000; **p<.01; * p < .05.

We on most accounts find systematic differences in attitudes across position in the municipality. For all three dimensions, leading officials differ significantly from other position. For Individualisation and Centralisation, they score higher than other positions, whereas they score lower on Localisation. We also see that there are significant differences in Individualisation and Centralisation between Board members and Committee members. All of this suggests that service attitudes differ depending on position in the municipality and thereby corroborates H1. It is, however, worth noting that the specific effects depend on the mode of service attitude under consideration.

Next, we explore the differences with the help of multilevel regression analyses to further test H1 and examine the differences in effects across the context made up by the municipalities in the form of population size (H2) and economic status (H3). We show the specific effects in coefplots (Jann 2014) while the regression models are shown in the appendix. We first report the direct effects in Figure 1.

Figure 1. Coefplots showing multilevel regression results.

We see that the differences decrease when we consider other factors. This suggests that the existing differences are at least to some extent because people occupying specific positions tend to hold certain socio-demographic characteristics as well. Despite the weakening effects, it is also worth noting that some differences persist to be significantly different. For Individualisation, there are significant differences between leading officials and committee members, since the former are more positive towards more individualisation in service provision (B = −0.95, p = 0.025). The differences between leading officials and council members are also close to significance (B = −0.83, p = 0.050) with the former again being more positive. For Centralisation, there are no significant differences at a traditional p < 0.05 threshold, although the difference between leading officials and committee members comes close (B = −0.89, p = 0.059). For Localisation, we see that leading officials are more negative towards more local service provision than committee members (B = 0.96, p = 0.035), while the differences between leading officials and council members (B = 0.85, p = 0.060) and board members (B = 0.77, p = 0.089) are just above the conventional threshold. It is also worth noting that the effects are quite strong (up to one standard deviation), but the confidence intervals are also wide, indicating that other factors are also relevant in explaining welfare attitudes. The results also show that the main division of opinion is between leading officials and the rest, as board member, council members, and committee members have fairly similar opinions (no significant differences persist when taking into account other factors).

Taking together with the descriptive differences detailed above, we take this as support for our first hypothesis.

The subsequent question is whether the differences depend on contextual factors as proposed by H2 and H3. Figure 2 shows the results of the interaction effects. To make the figures easier to comprehend, we here only show the results for the interactions and the constitutive terms, but the regression models also include the control variables, as shown in the appendix.

Figure 2. Coefplots showing regression results for interactions.

There are no significant interaction effects for Individualisation, which suggests that the impact of position is similar across municipal size and economic situation of the municipalities. Under all circumstances, we may expect leading officials to be more positive towards service provision that favours less municipal effort in the process.

For Centralisation, there are significant interaction terms between position and municipal size, suggesting that the impact of position differ across municipal size (Board member x More than 100,000B = −0.59, p = 0.020; Council member x more than 100,000B = −0.85, p < 0.001). When it comes to Localisation, there is some evidence that the impact of position differs depending on the economic situation of the municipality (committee member x crisis B = 1.36, p = 0.012). To show what these significant differences entail in practice, we in Figure 3 show the predicted scores depending on position and contexts.

Figure 3. Predicted scores for centralization and localization across position and contexts.

The results for Centralisation show that leading officials grow more positive towards centralised service provision as the size of the municipality increases. For other positions, there is a small increase from small to intermediate sized municipalities, but this effect does not persist for the largest municipalities, where the differences are meagre and council members even grow more negative towards centralisation when they are in a large municipality.

For Localisation, leading officials grow more negative towards local service provision as the economic situations worsen. The same is also true for council members, whereas committee members become more in favour of local service provision as the economic situation deteriorates.

Hence, both H2 and H3 are at least partly supported since there are clear indications that the relationships between position and attitudes to service provision are at least to some extent contingent on key characteristics of the municipality.

Conclusions

These results have important implications for the credibility of Miles’ Law (Miles 1978), or the idea that position matters for attitudes, even for municipal decision-makers. We clearly demonstrate that position matters for attitudes on service provision. We see that there are important differences between decision-makers within the municipal organisation, depending on whether they are members of the council, members of the executive board, members of committees or the leading officials in the municipality. We also show that these differences between positions persist in all dimensions of attitudes on service provisions. While previous studies have indicated that the position may play a role both in Finland and elsewhere (Berman, Martin, and Kajfez 1985; Pikkala 1997; Sandberg 1997; Ståhlberg 1997; Pikkala 2005; Sandberg 2012; Bowman 2017), this is to our knowledge the first study to examine the applicability of Miles’ Law for decision-makers. This shows that Miles’ Law has applicability beyond civil servants and thereby opens up a fruitful new research agenda with the aim to examine how positions can affect the attitudes and behaviour of elected officials.

It is noteworthy that the relationships between position and attitudes persist even when taking into consideration party support, showing that the differences are not driven by dominant parties or ideological affinities. This shows that the position a person occupies within the municipality has an independent impact on preferences for service provision irrespective of ideological affinities, which is otherwise often assumed a salient characteristic. This may help explain why ideology and partisanship has appeared to be less relevant than what may otherwise be expected (Fredriksson et al. 2010; Granqvist 1997). The perspective shared by people in the same position may do more to shape attitudes and behaviour than the party affiliation.

Furthermore, we demonstrate that these relationships are at least to some extent contingent on contextual characteristics of the municipality such as size, which is in line with previous studies emphasising the important differences between municipalities (Giritli Nygren and Nyhlén 2017; Hirvonen, Karhila, and Saukkonen 2016; Fredriksson et al. 2010). The impact of position is accentuated by the size of the municipality in terms of population. Leading officials in larger municipalities prefer using Centralisation for service provision more than others, who were less enthusiastic. However, it is possible that the effect of municipal size is in fact explained by distances. In larger municipalities, centralisation is easier because everything is close. We also find that reactions to economic hardship differ across positions when it comes to attitudes to Localisation. This shows that it is imperative with nuanced analyses to appreciate the subtle impact of the position to appreciate the importance.

While not part of main aims, it is also worth noting that we corroborate the suggestion that attitudes to service provision is a multidimensional concept (Svallfors 2011). This entails that more general questions on welfare services only asking respondents whether they are for or against welfare (e.g., Jakobsson and Kumlin 2017) fail to recognise that welfare opinions consist of multiple separate dimensions and may therefore also fail to capture the impact of positions.

All of this demonstrates that it is important to examine in future research how the position of decision-makers affect their attitudes on a range of topics beyond service provision. It is also worth noting that Finland constitutes a particular case, both when it comes to the local administrative structure and the electoral system. It is therefore important to replicate these results in a different context, both in different policy sectors and preferably in a comparative perspective that include several countries to be able to assess how country characteristics affect the findings. This would, for example, make it possible to examine whether Miles’ Law only operates under open-list proportional representation electoral system (von Schoultz and Papageorgiou 2019), or is an effect of the council-manager administrative system (Mouritzen and Svara 2002: 56, Howard and Sweeting 2007; Sellers, Lidström, and Bae 2020).

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Chen (2012, 242) includes a parenthesis in a footnote saying: ‘Allison credits Paul Hammond, but Miles claims original authorship’. This is incorrect, because the footnote referring to Paul Hammond is nr 83. In footnote nr 82, however, Allison (1969, 711) wrote: ‘This aphorism was stated first, I think, by Don K. Price’, commenting the phrase in question. Further, the text by Machol (1978, 86) was apparently published before Miles’ own article, as Machol begins ‘According to the Wall Street Journal (Feb.22, Dahl and Tufte 1973), Miles’ Law was ‘promulgated some years back by Rufus Miles […]’’. Miles (1978, 399), again, mentions two persons in the story behind the phrase (occurring ‘in late 1948 and early 1949’), besides himself. One of them is the examiner who changed his position, the other is an associate to whom Miles predicted the change in the examiner’s attitude. When Miles, at the point where this change had occurred, said to his associate ‘You see, it depends on where you sit, how you stand’, the associate (‘wide-eyed’) said “That deserve to be given the status of a law. You should call it ‘Miles’ Law’”.

2. A reform of the Finnish welfare system has transferred the responsibility for organising health and social services to a new, regional level from 2023.

3. In 2015 (when the material was collected) there were 301 municipalities in mainland Finland, with on average 17,500 inhabitants. The median size was 6,000 and only nine cities had more than 100.000 inhabitants.

4. The intra-class correlations for the three null models are 0.008 for Individualization, 0.005 for Centralization and 0.014 for Localization. These low levels of intra-municipal correlations indicate that it is unlikely that the situation of the municipality plays a major role.

5. There is some overlapping between categories since most board members are also members of the council (n = 329 out of 355) and many councillors are members of committees (n = 428). Since we assume that experiences from the most influential position is what affects their attitudes, they are coded accordingly.

Appendix

Table

	Individualisation		Centralisation		Localisation
	M1	M2	M1	M2	M1	M2
Position (ref. Leading official
Board member	−0.734	−0.673	−0.618	−0.237	0.776	0.415
	(0.424)	(0.453)	(0.473)	(0.504)	(0.456)	(0.491)
Council member	−0.825	−0.826	−0.700	−0.389	0.853	0.589
	(0.421)	(0.448)	(0.469)	(0.499)	(0.453)	(0.486)
Committee member	−0.949*	−0.934*	−0.892	−0.607	0.962*	0.325
	(0.424)	(0.459)	(0.472)	(0.513)	(0.456)	(0.500)
Gender	−0.133**	−0.131**	−0.0892	−0.0996	−0.264***	−0.263***
	(0.0475)	(0.0476)	(0.0529)	(0.0526)	(0.0511)	(0.0511)
Education	−0.0520	−0.0555	0.131	0.144	−0.0309	−0.0150
	(0.0776)	(0.0776)	(0.0867)	(0.0860)	(0.0838)	(0.0836)
Employment private sector	−0.00476	−0.00338	−0.0887	−0.0950	−0.0479	−0.0339
	(0.0527)	(0.0527)	(0.0587)	(0.0583)	(0.0567)	(0.0566)
Party affiliation (Ref don’t know)
KOKK	1.093**	1.109**	0.476	0.422	−0.886*	−0.770
	(0.418)	(0.419)	(0.466)	(0.462)	(0.449)	(0.449)
KD	0.528	0.552	−0.0326	−0.0399	−0.0611	0.0255
	(0.436)	(0.437)	(0.485)	(0.481)	(0.468)	(0.467)
PS	0.282	0.305	−0.138	−0.185	−0.0976	0.00653
	(0.421)	(0.422)	(0.469)	(0.465)	(0.452)	(0.451)
RKP	0.484	0.459	0.0888	0.0132	−0.576	−0.440
	(0.423)	(0.424)	(0.472)	(0.468)	(0.456)	(0.454)
KESK	0.602	0.626	−0.00383	−0.0875	−0.313	−0.176
	(0.418)	(0.419)	(0.466)	(0.462)	(0.450)	(0.449)
SOCD	−0.208	−0.191	0.277	0.214	−0.00842	0.125
	(0.418)	(0.419)	(0.466)	(0.462)	(0.449)	(0.449)
LEFT	−0.916*	−0.902*	−0.362	−0.438	0.517	0.650
	(0.424)	(0.425)	(0.473)	(0.469)	(0.456)	(0.456)
GREEN	0.0982	0.111	0.119	0.0606	−0.265	−0.141
	(0.425)	(0.425)	(0.473)	(0.469)	(0.456)	(0.456)
Size of municipality (ref. Less than 20,000)
20,000–100,000	−0.0366	−0.0832	0.280***	0.383*	−0.408***	−0.491**
	(0.0628)	(0.140)	(0.0778)	(0.163)	(0.0819)	(0.161)
More than 100,000	−0.169*	−0.124	0.284**	0.840***	−0.276**	−0.339
	(0.0738)	(0.166)	(0.0929)	(0.196)	(0.0989)	(0.194)
Economic crisis situation	−0.0982	0.0199	0.227	0.518	−0.123	−0.692
	(0.160)	(0.372)	(0.202)	(0.438)	(0.215)	(0.433)
Interactions
Position # Size
Board member # 20000–100,000		0.0933		−0.101		−0.0608
		(0.177)		(0.208)		(0.206)
Board member # More than 100,000		0.0977		−0.544*		0.0705
		(0.213)		(0.254)		(0.252)
Council member # 20000–100,000		−0.0138		−0.256		0.135
		(0.165)		(0.197)		(0.195)
Council member # More than 100,000		−0.0992		−0.864***		0.196
		(0.191)		(0.232)		(0.231)
Committee member # 20000–100,000		0.0959		0.120		0.203
		(0.183)		(0.217)		(0.215)
Committee member # More than 100,000		−0.0830		−0.305		0.0632
		(0.208)		(0.250)		(0.249)
Position # Economic crisis
Board member # Economic crisis situation		−0.439		−0.619		0.804
		(0.477)		(0.565)		(0.561)
Council member # Economic crisis situation		0.0273		0.115		0.168
		(0.434)		(0.523)		(0.520)
Committee member # Economic crisis situation		−0.179		−0.809		1.257*
		(0.453)		(0.550)		(0.548)
Constant	0.650***	0.625***	0.276*	0.0492	−0.0416	0.155
	(0.113)	(0.160)	(0.130)	(0.183)	(0.130)	(0.180)
lns1_1_1
Constant	−2.535***	−12.96	−2.055***	−1.972***	−1.879***	−1.865***
	(0.606)	(395.5)	(0.346)	(0.341)	(0.238)	(0.289)
lnsig_e
Constant	−0.192***	−0.189***	−0.0854***	−0.0980***	−0.122***	−0.129***
	(0.0195)	(0.0191)	(0.0195)	(0.0201)	(0.0194)	(0.0202)
Observations	1372	1372	1372	1372	1372	1372
AIC	3417.6	3432.7	3718.9	3710.7	3625.4	3634.5
BIC	3522.1	3584.2	3823.4	3862.2	3729.9	3786.0