Power and buzz: Analysing trade union HQ locations by closeness to power and by convenience store score

When Hans Spekman ran for chairman of the Dutch Social-Democrat party in 2011, he said he wanted to move the party’s headquarters from the posh office at the Herengracht in Amsterdam to a «normal district, a neighbourhood where things happen, like Bos en Lommer». Bos en Lommmer is a multicultural neighbourhood in the west of the city, in transition from deprived to gentrified.

I agree with Spekman (at least on this matter) and I think his ideas about locations should also apply to trade union headquarters. Out of curiosity I decided to analyse the headquarters locations of European trade unions, using two criteria. First: closeness to power, operationalised pragmatically as the walking distance from the union office to the national parliament. And second: the liveliness of the neighbourhood. For measuring this I propose the convenience store score, which assumes that the number of convenience stores within half a kilometer gives a rough indication of how lively a neighbourhood is. Convenience stores could be for example 7-Eleven or AH to go stores and some ethnic shops will also be classified as convenience stores.

The chart below shows the scores for each union. You can also see the locations of union offices, parliaments and convenience stores on an interactive map, but note that the map may take a while to load - it’s not very suitable for viewing on a smartphone.

The median union headquarters is within 2km walking distance from parliament. For about three-quarters of unions, the distance is below 5km. The general pattern thus seems to be that unions have their national offices close to the institutions of political power. There are exceptions though. Officials of the major Dutch federations FNV and CNV would have to walk 15 to 68km to reach parliament. And sometimes the distance is even longer: a Basque union has its HQ in Bilbao; a Turkish union in Istanbul and Polish union Solidarnosz has its HQ near the port of Gdansk, where it originated. But all in all, the large Dutch unions are quite exceptional in that they don’t have their headquarters near the centre of political power.

As for liveliness: the median number of convenience stores within half a kilometer from union headquarters is 2, but about one in three unions have no convenience stores nearby at all. Some of the most lively union office locations are in countries like Romania, Hungary and Bulgaria. Other examples are CFDT (France), TUC (UK), SAK (Finland) and UGT (Spain). Dutch unions are at the other end of the spectrum and have rather dull headquarters locations - judging by the convenience store score.

So where should a union be? I’d say that influencing the government is one of the tasks unions should be doing, and an important one at that. However, this doesn’t depend on having a headquarters close to parliament, but rather on the ability to mobilise workers. I’d argue that the convenience store score is a far better criterium to judge headquarters locations by.

In case you were wondering: Spekman was successful in his bid for the chairmanship of the Social-Democrat party. The party’s headquarters is still at the Herengracht, though: it turned out the lease doesn’t expire until 2018.

Full disclosure: I work at the FNV, at the former FNV Bondgenoten location.


This analysis turned out to be quite a bit more challenging than I initially thought, but it was very instructive. I’m especially happy that I now have a basic understanding of the Overpass API that you can use to retrieve Open Street Map data. OSM has always been a bit of a black box to me but the Overpass API turns out to be a valuable tool.

Measuring neighbourhood characteristics

Initially I wanted to use Eurostat regional stats to analyse neighbourhood characteristics, but Eurostat doesn’t have data beyond the NUTS 3 level (I should’ve known). Level 3 areas may comprise entire cities and are useless for analysing neighbourhoods, so I had to look for alternatives.

Subsequently, I tried getting the name of the smallest area a location is in using the Mapit tool (based on Open Street Map). I thought I might then be able to construct a Wikipedia url by adding the name to This turned out to work pretty well, not least because Wikipedia is quite good at handling different variants of geographical names. However, while Wikepedia articles tend to be informative, they do not contain a lot of uniform statistical information. Often population, area and population density will be included, but not much beyond that. In addition, the fact that the size of the areas varies poses problems. For example, the population density of a small area cannot be meaningfully compared to the density of a large area. In the end I did add the Wikipedia links to the popups on the map, but I continued looking for other ways to analyse neighbourhood characteristics.

One of the measures I ended up using is closeness to power, operationalised as the walking distance to the national parliament (in countries with a bicameral parliament, I used the location of the lower house). This was a pragmatic choice. An alternative would have been to use the location of ministries, but then I’d have to come up with a way to pick the relevant ministry.

For measuring the liveliness of a neighbourhood, I used the number of convenience stores within half a kilometer, using data from Open Street Map. Obviously there are some limitations to this method. For example, some countries will be mapped in more detail than others. Also, there will be inconsistencies in how shops are classified (cf this discussion in Dutch about how to classify stores of chains like Blokker).

Obviously, the convenience store score has not been properly validated. I’m not even sure whether objective measures of a neighbourhood’s liveliness exist. I checked this list of «coolest» neighbourhoods in Europe and all but one (Amsterdam Noord) have convenience stores nearby, but then again coolness isn’t the same as liveliness (I guess a neighbourhood can be uncool yet lively). Furthermore, being on a list of cool neighbourhoods isn’t necessarily an indicator of coolness.

Ideally I think a proper assessment of the convenience store score should include a comparison with measurements of criteria derived from Jane Jacob’s The death and life of great American cities: mixed primary uses, short blocks, buildings of various ages and density. I guess it should be possible to measure some of these with OSM data (especially the first two). However, that would require a deeper understanding of OSM classifications than I currently have.

Getting the data

While some of the data was obtained by good old-fashioned googling, some of it could be automated.

The starting point for the analysis was the list of affiliates of the European Trade Union Confederation (ETUC). Note that this includes unions in non-EU countries such as Turkey. Also note that I use the word union but most are in fact union federations (the FNV is a bit more complicated; a recent merger has partly done away with the federation structure).

The ETUC doesn’t seem to have a list of addresses on their website. They do provide urls for most of their affiliates. Still, looking up addresses was a bit of an adventure, especially for countries which use non-Latin alphabets (let me know if you find any errors).

For walking distances I used the Bing API. In a number of cases Bing couldn’t find a walking route or the distance seemed wrong. In those cases I manually looked up the distance in Google Maps. Here’s a sample url for getting information from the Bing API (replace KEY with API key).

I used the Overpass API (demo) of Open Street Map to get all nodes within 500m from the union HQs, which I used for counting the number of convenience stores. I also used the API for getting the coordinates of all convenience stores in all countries where the ETUC has affiliates. Here’s a sample url for getting all nodes within 500m of a location, and here for getting all convenience stores in a country.

A few unions are missing in the final results because of missing data. For example, I couldn’t figure out what the main office of the Belgian ACV is and I couldn’t find the exact location of the parliament of Malta (somewhere along Republic Street, Valletta).

Calculating scores

I calculated scores as either walking distance to parliament in kilometers or the number of nearby convenience stores. In both cases I took the log10 of the value + 1. To arrive at a 0 to 10 scale, I multiplied by 10 and divided by the maximum score for each variable. For the distance to power measure I converted the score to 10 minus the score, so that a higher score means closer to power.


I used Leaflet and D3.js to map the locations of HQs, parliaments and convenience stores. There are over 60,000 convenience stores in the dataset. This turned out to be a bit too much and the browser all but crashed. I found this script that deals with exactly this problem. While I managed to figure out what I needed to change to make the script work with my data, I’m afraid I don’t fully understand how it works. It’s still too slow for mobile, though.

Immigrants, filesharing and wiretaps: How newspapers use the word illegal

People should mind their language: an apparently neutral term like immigration has gotten xenophobic overtones as a result of its frequent use in combination with illegal, James Gingel argued in the Guardian. As an illustration, he pointed out that illegal, when typed into a Google search box, will likely get autocompleted to illegal immigrant or illegal immigration.

Earlier, the Guardian had been criticised for using the term illegal immigrant, among other things because it’s dehumanising. David Marsh of the Guardian Style Guide agreed. (The Style Guide itself takes a rather technical position on the matter: «… there is no such thing as an illegal asylum seeker … An asylum seeker can become an illegal immigrant only if he or she remains in Britain after having failed to respond to a removal notice.»)

Personally, I’d be in favour of reappropriating the term illegal immigrant - but it’s not for me to tell other people what strategy to use.

So how does the Guardian use the word illegal? I counted the words that follow the word illegal in their articles. I ignored stop words and in most cases I used stemming to lump together words like download, downloads, and downloading (see Method below).

The chart shows that the term illegal is most often used in combination with immigrant and variants. Other than that, it appears that illegal filesharing is a 2009 thing and that illegal phone [hacking] was an issue in 2011. Unsurprisingly, the expression illegal war started being used in 2003. By the way, what’s the status of that trial?

There’s also a bit of a peak in mentions of illegal thing in 2000. This can be attributed to a series of interviews in which one of the standard questions was «What was the last illegal thing you did?» The answers are somewhat boring, with the exception of «Shot a man in Reno just to watch him die» (a reference to Johnny Cash, of course).

The Guardian’s search API is largely limited to articles that appeared after 1998. For a longer term perspective, let’s turn to the New York Times, which offers access to the lead paragraphs of articles dating back to it’s origin in 1851.

That’s weird: expressions with the term illegal seem to have been rare until the 1970s. Either that, or I made an error in my analysis of the NYT data. I checked their own Chronicle tool, which confirms that the term illegal wasn’t used very much before the 1970s.

Again, the term illegal is mainly used in combination with aliens (1980s) and immigrants (2000s), but such uses seem to have dropped in the 2010s. My guess would be that this has to do with the growing importance of the «Latino vote», which means that politicians can no longer evoke negative images of immigrants without risking electoral consequences.

Speaking of vote: the expression illegal vote is one of the rare uses of the term illegal in the early days of the New York Times. Illegal voting appears to have been a recurrent concern in 19th century New York, as illustrated by a report from 1888:

Notwithstanding the widespread reports to the contrary and the wholesale issue of warrants for the arrest of illegal voters yesterday’s election in King’s County passed off without unusual excitement.

Tracking the use of the expression illegal strike provides an interesting insight into American social history: wildcat teachers’ strikes in the 1960s, broader public sector strikes in the 1970s and Reagan’s brutal standoff with air traffic controllers in the 1980s. Despite the progressive reputation it enjoys today, the New York Times often sided with law and order, for example in this 1962 report:

It was not a day New York City could be proud of. Half of the city’s 40,000 public school teachers had chosen an outlaw course and stayed away from their classrooms in an illegal strike. (If you’re wondering why public sector workers resorted to illegal strikes, read this article.)

The 1970s saw a modest peak in the use of the expression illegal wiretaps, often in connection with Watergate. In an article from 1974, the question was raised «whether President Nixon may have knowingly used claims of national security to cloak illegal wiretaps and other illegal surveillance». How modern.

So here’s my preliminary, non-scientific conclusion: newspapers appear to use the term illegal mainly to talk about immigrants, but when those in power really mess up, their actions will occasionally be called illegal too.


I used the search APIs of the Guardian and the New York Times to search for articles with the search term illegal. I counted the words following the term illegal, using the Python nltk library to exclude English stop words and to reduce words to their stem. A practical matter is that stemming will reduce both immigrant and immigration to immigr. Since some of the arguments against using the expression illegal immigrant do not apply to illegal immigration, it makes sense to differentiate between immigration and immigrant. Therefore, I separately counted occurances of the expression illegal immigrant[s]. Here’s the code.


Buttons FNV

Kijk aan, m’n foto van oude FNV-buttons (onderdeel van de mini-serie Retro FNV) illustreert een pleidooi op voor een strijdbare vakbeweging. Onderzoeker Matthias van Rossum zoekt onder meer inspiratie bij de Amerikaanse Fight for $15, een brede sociale beweging die de nodige successen heeft geboekt in de strijd voor een eerlijke beloning voor werknemers.

De FNV kan daar inderdaad een hoop van opsteken. Over de manier waarop je dat in de praktijk brengt, valt nog wel een discussie te voeren. Ik ben het bijvoorbeeld met Van Rossum eens dat de FNV een onderdeel moet zijn van een brede sociale beweging, die strijd tegen lage jeuglonen, tewerkstelling, discriminatie, en ga zo maar door. Tegelijk vind ik dat je in een campagne moet kiezen voor specifieke onderwerpen waar je op dat moment resultaten mee wilt bereiken (zoals de strijd voor $15 in Amerika). Van Rossum ziet dit, als ik het goed begrijp, als een onwenselijke inperking.

Lees het artikel hier.

Over het slopen van Amsterdamse School-blokken


Aan de Tugelaweg in de Amsterdamse Transvaalbuurt zijn een paar huizenblokken in de stijl van de Amsterdamse School gesloopt. Ik was er niet blij mee: we moeten zuinig zijn op de Amsterdamse School, zelfs als het niet om de hoogtepunten van de periode gaat. Maar eerlijk is eerlijk: de nieuwbouw die ervoor in de plaats is gekomen ziet er goed uit en past bij de blokken die gespaard zijn gebleven.

Aan de andere kant van de buurt, aan de Transvaalkade, was al iets vergelijkbaars gebeurd. Daar is de vervangende nieuwbouw zelfs een nauwkeurige kopie van de Amsterdamse School.

Maar terug naar de Tugelablokken. Na wat zoeken kwam ik erachter dat het besluit om te slopen niet zomaar is genomen: van te voren heeft ene J. Schilt van het gemeentelijk Bureau Monumenten en Archeologie een rapport opgesteld over de kwestie. In een compacte schrijfstijl en met oog voor interessante details beschrijft hij de geschiedenis van de woningen.

De Tugelablokken zijn tussen 1915 en 1924 gebouwd door de Handwerkers Vriendenkring (HWV), een instelling met wortels in de joodse arbeidersbeweging. De HWV heeft nog aan de wieg gestaan van één van de eerste vakbonden in Nederland, de Algemene Nederlandse Diamantbewerkersbond, een voorloper van de FNV. De HWV mocht een deel invullen van het plan dat H.P. Berlage had gemaakt voor de nieuwe buurt.

Destijds lag de spoorlijn langs de Tugelaweg nog op het maaiveld; die is later pas opgehoogd. Die spoordijk verklaart waarom de Tugelaweg tegenwoordig een beetje claustrofobisch aandoet.

Tijdens de oorlog was de Transvaalbuurt eerst een concentratiegebied waar joden uit andere buurten gedwongen naar moesten verhuizen. Later is een groot deel van de bewoners gedeporteerd. «Vooral tijdens de hongerwinter vielen deze woningen vervolgens ten prooi aan houtroof, zodat na de oorlog delen tot ruïne waren vervallen.» De woningen werden deels opgeknapt maar de onbewoonbare bovenste verdiepingen werden gesloopt, met hoogteverschillen als gevolg. Schilt schrijft hierover:

De oorspronkelijke architectonische uitstraling heeft uiteraard geleden door de noodzakelijke herstelwerkzaamheden kort na de bevrijding, welke bouwsporen echter ook de herinnering aan de oorlogsjaren en vooral het lot van de joodse bevolking levend houden.

Uiteindelijk kwam Schilt tot de conclusie dat sommige blokken gespaard moeten worden en dat eventuele nieuwbouw moet passen in de buurt:

Het resultaat zou in ieder geval een vorm van «Stadtreparatur» moeten zijn, oftewel een vorm van behoedzame stadsvernieuwing, en niet de een of andere eigenwijze en eigentijdse visie van een sterarchitect.

Hoe dan ook is het goed om te weten dat de gemeente blijkbaar betrokken en deskundige mensen in dienst heeft om over de sociale geschiedenis te waken.

Op de foto zie je de nieuwe blokken vanaf de Retiefstraat; de Tugelaweg zie je vanuit de trein tussen Amstel en Muiderpoort.