In France, the notion of ville moyenne (medium-sized city) has been elaborated since the 1970s. It was first created as a reference in territorial policies introduced by the central state that aimed to achieve polycentric spatial organisation in France (Vadelorge 2013: 33). After being used in policy programmes, this term emerged in research and progressively constituted a category of its own. This type of city can be defined according to three main criteria: their position in the urban hierarchy, their centrality functions, and their specific history and link with public policies. Indeed, medium-sized cities are defined, in France but also in many other countries, as being in an in-between position: they are neither metropolises nor small towns. This implies that they provide a variety of facilities or services, which gives them an influence on their surroundings (Santamaria 2012; Duroudier 2014; Tallec 2014; Demazière 2017). Therefore, medium-sized cities are often described as centres for the surrounding rural areas. Medium-sized cities in France can also be defined in relation to a specific historical and political context, which differentiates them from small cities or towns. Indeed, the urbanisation of medium-sized cities is strongly linked to the rural exodus and Fordist industrialisation (Santamaria 2012; Tallec 2014). During the 1950s and the 1960s, these cities attracted the workforce from the surrounding rural areas, as job opportunities in the newly established factories increased. This development was amplified by public policies, which participated in building discourses about these cities. The political ambition, which remained powerful for decades, was to develop these cities to create urban centres in rural areas, with the mission of providing public services and promoting territorial equilibrium and equity throughout France (Vadelorge 2013).

From the 2000s onwards, medium-sized cities re-entered French public discourses and policies through the angle of the devitalisation of city centres. Indeed, the centres and high streets of these cities started to be increasingly depicted in the media as spaces in crisis, presented as ‘deserted’ or ‘devitalised’. In 2017, the book “Comment la France a tué ses villes?” (How did France kill its cities?), written by journalist Olivier Razemon, reflects the mediatic coverage of this phenomenon. The author describes the “wounds of medium-sized cities”: the weakness of the city centre retail functions, with vacancies and a lack of diversity, the increase of housing vacancy rates and the pauperisation of the city centres are also cited (Razemon 2017: 61-77). This multidimensional crisis therefore affects the retail functions of city centres, but also the urban built environment and the population. It has been explained by the dynamics of the sprawl of housing and shops towards urban peripheries, and shifts in the consumption and transport habits of households. In particular, changes within the retail sector, such as the development of malls and hypermarkets, and the democratisation of cars have been pointed out as key to understanding these shifts (Bouvier/Madry 2017; Pointereau/Bourquin 2017; Razemon 2017).

City centre devitalisation also prevails in the discourses of public and institutional actors about medium-sized cities. At the national scale, the agenda setting of a ‘crisis of medium-sized cities’ has continued since 2008, with a focus on the devitalisation of city centres (Dormois/Fol 2017; Pointereau/Bourquin 2017). Since 2016, several reports about the devitalisation of medium-sized cities have been published (CGEDD/IGF 2016; Lestoux 2017; Pointereau/Bourquin 2017) and in 2017, the national programme “Action Coeur de Ville” (City Heart Action) was launched. It specifically targets the revitalisation of medium-sized city centres. In the subsequent five years, 230 cities were to benefit from funding and support for urban renewal projects in their city centres.

In the late 2000s, medium-sized cities also entered the scientific debate in France, but from a different perspective. Studies about urban shrinkage indeed drew attention to medium-sized and small cities, as these types of cities seemed to be more prevalent amongst shrinking cities than larger ones. According to the most recent analyses about demographic decline (Cauchi-Duval/Cornuau/Rudolph 2017: 3), small cities are the most affected, as they represent more than two thirds of shrinking cities in France and less than half of the growing or stable cities. Medium-sized cities are less concerned, but still represent 20 % of shrinking cities. As for large cities, they represent about 10 % of shrinking cities, and more than a third of stable or growing cities. In France, shrinking cities are concentrated in the north, north-east and the centre of the country, which are former industrial or remote rural areas. The development of a global production system has been analysed as a key to understanding urban shrinkage in France. Indeed, deindustrialisation induced a deep economic crisis in these territories, and their disconnection from global networks made their economic transformation particularly difficult (Cunningham-Sabot/Fol 2009; Miot 2012; Wolff/Fol/Roth et al. 2013; Cauchi-Duval/Cornuau/Rudolph 2017). Suburbanisation intensifies processes of urban shrinkage, as it contributes to the weakening of the city by causing demographic losses and a departure of wealthier households (Miot 2012; Fol/Miot 2014).

The literature about public services closures and state retrenchment has also highlighted the vulnerability of small and medium-sized cities in France with the multiplication of public management reforms since 2007 (Taulelle 2012; Barczak/Hilal 2017; Taulelle 2017; Baudet-Michel/Conti/Chouraqui et al. 2019). Public management reforms have been conducted in several countries of Europe, North America and Australasia since the 1960s (Pollitt/Bouckaert 2011). The content of these reforms varies amongst countries but, because they appeared in a specific economic context where state spending was considered inflated, several similarities appear. The New Public Management doctrine has, in particular, widely influenced the content of reforms. This “doctrinal puzzle” (Bezes 2009: 3) or the theory’s central principle is that the public sector can be improved by imitating the private sector (Bezes 2009; Pollitt/Bouckaert 2011). In France, new spatial distributions of public services were implemented with the “Révision Générale des Politiques Publiques”, a programme review inspired by New Public Management principles that was conducted between 2007 and 2012. This programme review’s main objective is to optimise public expenditure by reducing state spending when it is too costly and least economically viable. This resulted in public services closures, specifically where their maintenance was most expensive because of lower levels of activity. Rural areas were hit, but so were cities. Amongst cities affected by these reforms, an over-representation of small and, to a lesser extent, medium-sized cities has been demonstrated (Baudet-Michel/Conti/Chouraqui et al. 2019). To sum up, some public policies seem to favour a process of concentration of public services in more densely populated areas. Metropolises and large cities are, indeed, less affected by public service closures in France. In an economic context that already favours the agglomeration of people, activities and wealth in large cities, such trends may increase territorial inequalities and reinforce the difficulties faced by some small amd medium-sized cities or rural regions.

At the crossroads of these fields of research, several studies focusing on the shrinkage, decline or devitalisation of medium-sized cities emerged after 2010 (Baudet-Michel/Berroir/Fol et al. 2017; Guéraut 2018; Berroir/Fol/Quéva et al. 2019). They explored the different forms and dimensions of the decline of medium-sized cities, and presented these difficulties as resulting from global economic changes, public services reorganisations and suburbanisation. This paper also follows this line by investigating the different forms of decline in medium-sized cities and their specificity in comparison with large or small cities. More precisely, I concentrate on devitalisation and urban shrinkage processes, which have mostly been studied separately to define the decline of certain medium-sized cities in France. Therefore, their links, interactions and relationship to one another remain unclear. Is it possible to distinguish them from one another? What are their similarities and differences? Do they sometimes overlap?

Firstly, medium-sized cities were selected from all French cities, following the three criteria mentioned above: their in-between position in the urban hierarchy, the influence of the city on its surroundings, and historical specificity (in particular strong links with national public policies). Variables were associated with each criterion in order to transform this theoretical definition into an empirical one that would allow medium-sized cities to be distinguished from large and small cities in the French urban system.

The first criterion of definition (intermediate position in the urban hierarchy) was estimated by setting thresholds on the 2016 population of urban areas. The goal is to measure demographic thresholds that are specific to medium-sized cities and reflect their in-betweenness in the urban hierarchy. The French urban hierarchy respects the rank-size law, and is therefore characterised by a pyramidal shape (or Christallerian organisation) with very few large cities, numerous small cities, and medium-sized cities in between (Pumain/Moriconi-Ebrard 1997: 307). This shape makes indicators such as the mean or the median unsuitable for choosing thresholds for medium-sized cities, as these cities are not positioned in the ‘middle’ of the urban hierarchy, but closer to the top. Thus, thresholds were chosen using the observation of a rank/size graph to locate medium-sized cities (see Figure 1). More precisely, a rank size diagram of French urban areas with a non-logarithmic scale was used. The cloud of dots forms a curve that reflects the pyramidal shape of the urban system. The vertical part of the curve is constituted by numerous close dots, which are small cities; the horizontal part is formed by a few distinct dots, which are large cities. In between, the turn of the curve gathers medium-sized cities. A multi-linear regression was utilised to precisely locate the breaks in the curve, particularly around this turn. This method allowed demographic thresholds to be set for medium-sized cities. Urban areas with a demographic weight situated between 37,300 and 146,900 inhabitants were considered as occupying an in-between position in the urban hierarchy that characterises medium-sized cities.

The centrality and influence of cities on their surroundings was measured through the diversity of facilities and infrastructure they provide. This diversity was captured using the Permanent Database of Facilities and Equipment of 2018 (Base permanente des équipements), with indicators to measure the diversity of facilities within each French urban area. The database distinguishes three different ranges of facilities according to their occurrence within French municipalities: local, intermediate and superior. It gathers information about the services, shops or infrastructure located in each French municipality. An indicator that measures the diversity of facilities in each range was built, and thresholds were set to distinguish high levels of diversity from lower levels.

Finally, the link to public policies and the importance of discourses which participated in creating the category of medium-sized cities in France were integrated in the definition with a variable indicating whether urban areas have benefited from at least one of the two national programmes aimed at medium-sized cities since the 1970s.

The programme Action Cœur de Ville (2017) and the Contrats de villes moyennes (1973).

Secondly, two classifications were conducted on French urban areas’ subsets, in order to qualify their socio-economic composition and their demographic evolution. The socio-economic classification clusters subsets according to their socio-economic composition in 2016, using multivariate analysis methods. The variables chosen for this classification were those that differed more strongly between observations. Unemployment was selected to capture the local economic situation with a synthetic indicator, and three out of the six groups of the standard occupational classification

Nomenclature des professions et catégories socioprofessionnelles.

The demographic evolution classification groups statistical items according to their demographic trajectories.

TramineR package on R.

For both classifications, the method is designed to account for the homogeneity or heterogeneity of French urban areas

An urban area is a functional delimitation of cities created by the French national institute of statistics and economic studies (Insee). An urban area is a group of contiguous municipalities, encompassing an urban core providing at least 1,500 jobs (the urban unit), surrounded by peripheries, among which at least 40 % of the employed resident population works in the urban core.

For both classifications, the results obtained allow the urban areas’ subsets (central municipalities, banlieues and peripheries) to be categorised in different clusters, according to their socio-economic composition and demographic trajectory. However, our goal was to qualify the urban areas as a whole. Therefore, sequence analyses were conducted to identify the most common sequences of clusters within urban areas, and to group those which were similar. This allowed to elaborate more readable and synthetic results at the urban area level, while still taking the heterogeneity of urban areas into consideration (see Figure 3).

Eventually, the clusters of these two typologies were intersected for medium-sized cities in order to create a unique classification that synthesises the most common combinations of demographic and socio-economic classes.

In this classification, unemployment rates tended to be quite independent from other variables, which is why a partition was necessary in a high number of classes to obtain the most robust results. A partition in eight clusters was chosen for this reason (see Figure 4).

This high number of classes allows some clusters that are relevant for the analysis to be isolated, and other clusters to be grouped together. As a result, a partition was adopted in four classes (see Table 2). The socially privileged class gathers together clusters 1 and 2. The mixed and socially diversified class gathers clusters 3, 5 and 6. It groups together a socially mixed cluster (cluster 3, which includes subsets with close to average rates for workers, intermediate professionals, and executive staff and highly educated professionals) and two clusters characterised by strong social specialisations (in clusters 5 and 6, workers and intermediate professionals are respectively overrepresented). These clusters have lower than average unemployment rates in common. Cluster 4 was treated on its own, as a fragile class, where the share of workers, executive staff/highly educated professionals and intermediate professionals is close to average, but the unemployment rate is high (15 % in this class, compared to an average of 12 % for all statistical items). Finally, a pauperised class was created by grouping the classes 7 and 8, which are characterised by overrepresentations of workers, underrepresentations of executive staff, and high unemployment rates (on average 15 % in cluster 7 and 22 % in cluster 8).

These profiles are heterogeneously distributed amongst urban areas. Figure 5 shows that the more socially privileged type is predominant in large cities, rather present in medium-sized cities, and uncommon in small cities. In medium-sized cities, we notice important contrasts between the subsets of urban areas: whereas the fragile and pauperised types are predominant amongst central municipalities, privileged and mixed or socially diversified profiles prevail in more peripheral subsets. Finally, four synthetic classes defining the medium-sized urban areas’ socio-economic composition and spatial organisation were created in order to take into account these contrasts between central municipalities, banlieues and peripheries (see Table 3).

The second classification allowed subsets of urban areas to be distinguished according to their demographic trajectory. A division in five clusters was chosen (see Figure 6). Then, in order to make the analysis more readable, the types of most interest for the research question were isolated and others were grouped to obtain a partition into four groups (see Table 4). Cluster 1 was isolated and includes statistical items with growth trajectories. Clusters 2 and 4 were grouped together as both of them include mixed trajectories. Indeed, cluster 2 corresponds to slower growth trajectories: over the last intercensal period (2011-2016), 50 % of the headcount of this cluster was affected by demographic decline but with low average losses (‑0.15 %/year). Cluster 4 groups items with trajectories of interrupted demographic decline. Cluster 3 groups urban areas’ subsets with trajectories of demographic decline since 1975 or 1982. Cluster 5 includes trajectories with alternating periods of stagnation and decline, or recent decline (since 2006).

In this second analysis, we note more similarities between large cities, medium-sized cities and small cities than in the socio-economic cluster analysis (see Figure 7). However, small cities are distinguishable because of their low share of subsets with trajectories of demographic growth. The central municipalities of medium-sized cities are also noticeable, as 60 % of them belong to the decline or stagnation/recent decline clusters. The banlieues and outer peripheries of medium-sized cities are less affected by this phenomenon. Finally, four classes were created to define the demographic trajectories of medium-sized cities’ urban areas and their spatial heterogeneity (see Table 5).

The sixteen possible combinations of the two classifications and their distribution amongst medium-sized cities are represented in Figure 8. The analysis of this diagram guided us in elaboration of the final typology, presented in Table 6. More than 70 % of medium-sized cities can be considered as being in decline, and two main situations appear. Some urban areas are strongly affected by demographic and socio-economic difficulties: at least two out of the three subsets (central municipality, banlieue or peripheries) are affected. We decided to name these types ‘urban shrinkage’, as their characteristics are in line with the results of research about shrinking cities in France (demographic losses, high rates of unemployment, pauperisation of residents). In some urban areas, markers of decline are only present in the central municipality, but not in the close or outer suburbs: we decided to name these types ‘urban decline of the centre’, which can be more or less intense. This group of cities are likely to be affected by city centre devitalisation, as they are characterised by a pauperisation of their residents and demographic losses, but only in their centres. However, this result should be confirmed with analysis involving more variables, as city centre devitalisation is also characterised by other factors, such as commercial or housing vacancies.

Explorations of time series datasets allowed some specificities of these profiles to be highlighted. On average, urban areas affected by severe or limited urban shrinkage are characterised by very high rates of workers in the late 1960s, which suggests they were industrialised during the Fordist era. Moreover, these cities have displayed markers of decline

Such as demographic decline, rise of unemployment rate, social specialisation of the core of the urban area.

As seen above, several studies suggest that small and medium-sized cities tend to be more fragile than large ones (Cauchi-Duval/Cornuau/Rudolph 2017; Baudet-Michel/Conti/Chouraqui et al. 2019). The results presented in this paper support this idea: in both cluster analyses, large cities display the highest shares of growing or socially privileged clusters (see Figures 5 and 7). These differences between large and smaller cities are often explained by globalisation and metropolisation processes, which have reinforced the agglomeration of people, economic activities and wealth in metropolises and their regions (Scott/Storper 2003). Some large cities therefore become “centres of command and control” in globalised networks (Amin/Graham 1997: 413; based on Sassen 1991) and concentrate the most strategic economic functions. The development of metropolises may therefore overshadow smaller cities, whose economic specialisation and position within global networks are less favourable (Martinez-Fernandez/Audirac/Fol et al. 2012; Wolff/Fol/Roth et al. 2013). In France, the focus of territorial public policies on metropolises in the last ten years and the reorganisation of public services in favour of more concentration in larger cities enhance these tendencies, and can also explain the contrasts between large and smaller cities (Berroir/Fol/Quéva et al. 2019). This tendency is more generally observable in other countries (Kühn 2015; Lang 2015; Roth 2016). Scholars who focus on peripheralisation and polarisation processes in the European Union indeed underline that the reinforcement of metropolitan areas and their regions is a preferred policy to enhance European competitiveness at the international level (Lang/Henn/Ehrlich et al. 2015). If they are not compensated by spatial development policies for other territories, such policies that accompany and advantage already polarised regions can reinforce existent regional disparities. In France, territorial public policies followed these tendencies. The focus on re-equilibrium and territorial equity has become progressively less significant, and spatial policies favouring competitiveness have gained more and more importance (Santamaria 2012; Artioli 2017). This search for competitiveness led to the implementation of excellence policies targeted towards larger cities, with the goal of promoting their inclusion and position within global economic networks. Small and medium-sized cities, which used to be targeted and supported by public policies, seem to be disqualified in these pro-competitiveness strategies (Santamaria 2012). The emergence of a new public policy that targets medium-sized cities in 2017 could, however, change this tendency.

The heterogeneity of medium-sized cities’ urban areas may, however, differentiate this kind of city from large and small ones. On average, the central municipalities of medium-sized cities are most affected by demographic decline, and they display the strongest rise in unemployment rate since 1968, in comparison with the subsets of large or small cities’ urban areas. Moreover, our results show that more than 56 % of medium-sized cities face some difficulties in their central municipalities, but not in their peripheries. Thus, markers of decline seem to be more concentrated in central municipalities in medium-sized cities than in other types of cities. This configuration exists in small cities but to a lesser extent, as the peripheral subsets of small cities’ urban areas are also affected by decline. In medium-sized cities, banlieue and the outer peripheries are very rarely classed in the most fragile clusters of both socio-economic and demographic classifications (see Figure 5 and 7).

This spatial organisation could be explained by urban sprawl, which may have impacted medium-sized cities specifically. Indeed, in France urban sprawl started during the 1960s in large cities, and in other cities after 1970 (Haran/Garnier 2018: 28-29). Such suburbanisation may provoke a pauperisation and demographic decline of urban cores, because of the departure of middle and upper classes who are able to access homeownership in the peripheries. This contrast between declining centres and privileged peripheries is rarely observed in France’s largest cities, as the results presented here and other research show. Cusin (2016) indeed analyses French urban areas’ socio-spatial organisation by using real estate prices, and shows that the largest French cities

Paris, Bordeaux, Lyon, Nantes, Toulouse, Strasbourg, Rennes.

To sum up, medium-sized cities are not specific amongst French cities in terms of decline dynamics, because they share similarities with small cities, which also display markers of decline. At the same time, medium-sized cities seem to be specific in their socio-spatial configuration, as pauperisation and demographic decline of their centres affect a majority of them.

The results allow a distinction to be drawn between the devitalisation of city centres, on the one hand, and urban shrinkage, on the other hand. So far, the distinction between urban shrinkage and city centre devitalisation has been unclear. First, they have mainly been studied separately. Indeed, most government or institutional reports about medium-sized cities focus on the commercial devitalisation of city centres. Their analyses are limited to shop vacancies and conducted at intra-municipal levels (CGEDD/IGF 2016; Bouvier/Madry 2017; Pointereau/Bourquin 2017). Because of this specific focus, urban shrinkage is not mentioned in such reports. Scholars interested in the weakening of some medium-sized cities have mainly focused on urban shrinkage or urban decline. But after 2014, the growing tendency towards the devitalisation of city centres has been taken into account by some academics, who try to integrate this issue into their work and link it with urban shrinkage. In particular, the work of Baudet-Michel, Berroir, Fol et al. (2017) was the first to combine this notion with city centre devitalisation. Their work shows how the devitalisation of city centres can be a symptom of a more structural crisis affecting shrinking cities. This conclusion is in line with the majority of studies about urban shrinkage in France. Indeed, numerous previous studies show that the multidimensional crisis that characterises urban shrinkage is more intense in urban cores, which concentrate a poorer population, more significant population losses and more degradations of the urban environment (housing and retail vacancies, deterioration of buildings) than the peripheral areas (Fol 2012; Miot 2012; Wolff/Fol/Roth et al. 2013; Cauchi-Duval/Béal/Rousseau 2016). City centre devitalisation can therefore be considered as a manifestation of urban shrinkage; the two phenomena can overlap.

The results of this study show these two processes could also exist separately, as they are different in several ways. Indeed, medium-sized cities affected by urban shrinkage are characterised by an important fragility of their city centres, but other parts of the urban areas are also affected. This type of city is concentrated in a few regions. These cities have faced difficulties for a long time, with 1975 as a key date where markers of decline appeared. On average, such cities display a specificity in their social composition, with high rates of workers at the end of the 1960s (on average 48 %, compared to 40 % for medium-sized cities

Insee, Population census of 1968.

Medium-sized cities affected by city centre devitalisation are characterised by distinct features. First, difficulties are restricted to the central municipality, and increased strongly at the turn of the 2000s. Second, these cities are distributed throughout France and are not concentrated in particular regions. They do not display a specific social composition either. It can therefore be hypothesised that this form of urban decline is specific, as its temporality and geography differs from urban shrinkage. Such city centre devitalisation dynamics could be linked to the economic turmoil of 2008 which may have induced a pauperisation of fragile households living in city centres. A second wave of suburbanisation, particularly strong in medium-sized cities, is also observable at the turn of the 2000s (Haran/Garnier 2018: 28) and may have increased the demographic decline and pauperisation of medium-sized cities’ centres in the 2000s and 2010s.

These results therefore suggest that the two phenomena can be differentiated and are characterised by their own specificities. Other analyses could complete these results and allow the two phenomena to be distinguished more precisely. In particular, using data about the degradation of the urban environment seems pertinent. Case studies and field work could also improve knowledge about similarities and differences between these two processes and their history. International comparisons could also help to enhance understanding of the two processes.