In 1960, 29 Dutch MPs had a trade union background. Today, nine

After the Second World War, almost one in five members of the Dutch Lower House had a trade union background (in 1956, the Lower House expanded from 100 to 150 members). Then change set in. In 1960 there were 29 MPs with a trade union background; today nine.1 The largest decline was between 1960 and 1980.

The position of workers hasn’t gotten any better since 1980 - partly as a result of government policies.2 More workers have precarious jobs, the social safety net has been reduced and workers receive an ever smaller share of the proceeds of their labour. In many sectors, deregulation and privatisations have produced cut-throat competition, at the expense of workers. Austerity has deteriorated the quality of public services and destroyed jobs.

The key task of unions is to help workers organise so they’re not powerless vis-a-vis their employers. But in many ways, politicians set the rules that govern the labour market. Therefore, Dutch unions should probably engage more actively in politics - for example by mobilising their members to vote in elections. Further, it’s important to train union members for leading positions within the union and in politics.


The analysis is based on the resumes of post-WWII members of the Lower House published on I counted occurances of the following union federation names: 'FNV', 'CNV', 'NKV', 'NVV', 'EVC', 'RKWV', 'KAB'.

Some notes:

  • I didn’t count mentions of unions affiliated to these federations - that would hardly be feasible given given how many there are and the changes that have occured over time;
  • I manually excluded a number of cases where names of union federations occured in resumes. Reasons include: the reference was to an organisation with a name that is identical to one of the union federations’ names; someone merely sat on a joint committee of a political party and a trade union; etcetera;
  • I did not include the small unions / union federations that represent high-educated professionals, but including them would have had a negligeable effect on the outcome.

I recorded the start and end date for each period any of these persons was a member of the Lower House. Then I defined periods using all those dates as partitions (I ended up with over a thousand periods). For each period, I checked how many people with a union background were members of the Lower House during that period.

  1. In some European countries, the relation between politics and the union movement is dominated by the social-democrat party. In the Netherlands, there are also many christian-democrat MPs with a union background. Their number shows a similar development as the number of social-democrat MPs with a union background. The current MPs with a union background are Harm Brouwer (PvdA, FNV), Sjoera Dikkers (PvdA, CNV), Fatma Koser Kaya (D66, FNV), John Kerstens (PvdA, FNV) Jesse Klaver (GroenLinks, CNV), Pieter Omtzigt (CDA, CNV), Michel Rog (CDA, CNV), Paul Ulenbelt (SP, FNV / NVV) and Linda Voortman (GroenLinks, FNV).

  2. That’s not to say that the background of MPs directly influenced government policy - the relationship may well be more complex.


Has Google Maps found a way to have its cake and eat it

PL Takbuurt

Not interesting: P.L. Takbuurt

Google Maps are for transportation; Apple Maps are more of an advertising channel, I tweeted a while ago. That was based on a fascinating analysis by Justin O’Beirne, who found, among other things, that Google Maps show far more rail and underground stations, while Apple Maps show far more restaurants and shops.

However, things may have changed in a way. The CityMetric blog of the New Statesman reports that Google has been adding orangey areas to its maps. As Google explains, they represent areas of interest:

Whether you’re looking for a hotel in a hot spot or just trying to determine which way to go after exiting the subway in a new place, areas of interest will help you find what you’re looking for with just a couple swipes and a zoom.

We determine areas of interest with an algorithmic process that allows us to highlight the areas with the highest concentration of restaurants, bars and shops. In high-density areas like NYC, we use a human touch to make sure we’re showing the most active areas.

Assuming they haven’t sacrificed any stations, this suggests they have found a way to have their cake and eat it: remain useful for transportation purposes while adding marketing opportunities.

However, CityMetric writer John Elledge is not impressed by Google’s algorithm to identify areas of interest. He argues that «an algorithm that thinks Trafalgar Square is less an area of interest than the restaurants across the road is not fit for purpose».

As for Amsterdam, Google’s algorithm seems to be relatively good at identifying lively neighbourhoods, although they may have missed a few. On the other hand, the Museumplein, where the Rijksmuseum, Van Gogh Museum and Stedelijk are, isn’t marked as interesting, but then I’m sure tourists don’t need Google Maps to tell them to go there. Some of the most spectacular examples of Amsterdam School architecture (around P.L. Takstraat, Zaanhof) are similarly overlooked. By contrast, rather dull shopping centres such as Oostpoort are marked as interesting.

All in all, the correct designation for Google’s orangey areas would perhaps be commercial areas rather than areas of interest.


Users versus programmers: lon,lat or lat,lon

Somebody at Mapbox wrote a blog post in which he makes the case that longitude should go first: almost all data formats (including Google’s KML) and all open source software (except Leaflet) use this order. Also, it’s the logical order if you include altitude (XYZ), he argues.

Of course, it can’t be that simple, as this debate on Stack Overflow illustrates. It seems that programmers prefer lon,lat while people who use maps - seafarers, Google Maps users - expect lat,lon. As one commenter puts it:

Good rule of thumb: if you know what a tuple is and are programming, you should be using lon,lat. I would even say this applies if your end user (say a pilot or a ship captain) will prefer to view the output in lat,lon. You can switch the order in your UI if necessary, but the overwhelming majority of your data (shapefiles, geojson, etc.) will be in the normal Cartesian order.

Another good rule of thumb: always check.


Is it still ok to ridicule pie charts

Workers without job security as a percentage of all working people in the Netherlands. The pink slice shows the percentage in 2003; the red slice how much this has increased since. Data Statistics Netherlands, chart Relaunch animation.

In a series of articles that caused a bit of a commotion among chart geeks, Robert Kosara summarised the findings of a number of studies on pie charts. In one of the articles, he observes:

Pie charts are generally looked down on in visualization, and many people pride themselves on saying mean things about them and the people who use them.

I guess I’m one of those people who look down on pie charts. Sure, I’m not as outspoken as the respected Edward Tufte, who famously wrote that «the only worse design than a pie chart is several of them». I’m not always against pie charts and I’ve even experimented with animated pie charts to illustrate change in a proportion. But I’m not above making lame jokes about pie charts either. My rule of thumb would be: don’t use pie charts - unless you can come up with a good reason why you should use one in a particular situation.

Kosara describes a number of studies in which he measured how accurately people interpret pie charts and other charts showing a proportion, e.g. 27%. According to his findings, exploded pie charts are doing worse than regular pie charts (phew!) and square pie charts are doing better. Interestingly, a stacked bar chart appears to be doing worse than a regular pie chart (note that a stacked bar chart depicting a single proportion amounts to something that looks like a progress bar).

It’ll be interesting to see how this holds up in future studies. But for now, the finding that (stacked) bar charts are doing worse than pie charts may come as a bit of a shock, for there appears to be a sort of consensus that bar charts are generally better than pie charts. Question is, better at what?

Workers without job security as a percentage of all working people in the Netherlands. Data Statistics Netherlands, chart

A bar chart is quite good at showing that the level of workers without job security in the Netherlands was higher in 2015 than in 2014. But which chart type is better at showing how much the share has increased between 2003 and 2015? Until recently I would have said «the bar chart» without hesitation, but now I’m not so sure anymore.

That said - I think it’s still ok to ridicule 3D exploded pie charts.

Robert Kosara summarises his findings here and here. The recent studies were done in collaboration with Drew Skau; an older study in collaboration with Caroline Ziemkiewicz. The Tufte quote is from his book The Visual Display of Quantitative Information. The charts above show workers with permanent jobs and a fixed number of hours per week, as a percentage of all working people in the Netherlands (not just employees), source CBS.

Should freedom of information apply to algorithms?

[Update below] - Governments increasingly use data analysis to make decisions that affect citizens. But how transparent are these practices? In a study summarised here, Nicholas Diakopoulos had students file freedom of information requests to obtain, among other things, the algorithms behind government decision-making. Most requests were denied, for a variety of reasons. Some states claimed algorithms aren’t «documents» covered by FOI legislation; others said they were copyrighted.

The article reminded me of the risk profiles Dutch municipal welfare agencies use to decide who to submit to rigorous checks - including very intrusive home searches. As early as 2006, I was involved in a survey by Dutch trade union FNV which found that two in five municipalities used risk profiles for that purpose:

This has the advantage that for a large group of people, unnecessary routine checks can be dispensed with. However, there’s virtually no debate about what criteria can be used without causing unacceptable unequal treatment. Is it ok to select people because they’ve worked in the catering industry, or as a self-employed person? Or because of their nationality?

When the government uses algorithms exert control over citizens (or when they outsource that task, for that matter), there should be accountability. So would it be possible to obtain such algorithms through an FOI request?

I found one decision that suggests that algorithms aren’t a priori excluded from FOI requests - at least so in the eyes of the Utrecht municipality (I used Open State’s FOI search engine to find it). But welfare recipients’ organisation Bijstandsbond informed me that an FOI request has been filed in the past to obtain the risk profiles used by the Amsterdam municipal welfare agency. The request was denied.

[Update 2 July 2016] - Aside from the question whether you can FOI an algorithm, in Europe it may become possible to ask for «an explanation of the decision reached after [algorithmic] assessment» as a result of the EU’s General Data Protection Regulation, according to this analysis. Not only would this create more transparancy; it would also put technical constraints on programmers in that their algorithms have to be interpretable.


Amsterdam has room for another 2.1 million bicycle racks


Amsterdam has a persistent shortage of bicycle racks. Bicycle professor Marco te Brömmelstroet argues that this is really a matter of making choices: the space occupied by four parked cars could easily accommodate 30 bicycle racks.

Amsterdam is a compact city where space is limited. An important goal of the city administration is to create more room for pedestrians and cyclists, but also for green areas.

It so happens that the city of Amsterdam has recently published open data on on-street parking spaces. The data confirms what we already knew: parking spaces for cars occupy a huge amount of public space. The streets of Amsterdam are littered with as many as 265,225 parking spaces. If you exclude the ones with signs (spaces for charging car batteries; car sharing; etcetera), there are still 260,834 of them.

Assuming that each of them could accomodate at least 8 bicycle racks, there’s room for another 2.1 million bicycle racks. Now you probably wouldn’t want to remove all parking spaces and replace them with bicycle racks, but it does illustrate some of the choices that are available regarding the use of public space.

Map detail here.


The open data on on-street parking spaces is available in WFS format which is meant for creating maps but can also be used for downloading data - here’s a Python script that will do the job. I set the location of the parking spaces to the centre of the surrounding envelope.

I would have liked to display the data on an interactive map using Leaflet and D3js, but I’m afraid the quarter million data points would crash the browser. Instead I used OSM map data in combination with Qgis to display the parking spaces. Unfortunately, this means you can’t zoom in.

As for the parking space to bicycle rack ratio: I’m assuming a typical parking space takes up 12 to 14 m2. Cyclists’ organisation Fietsersbond has calculated that regular bicycle racks take up between 0.84 and 1.18 m2 per bicycle. The city of Amsterdam is a bit more conservative and estimates that a bicycle rack takes up about 1.5 m2, including the room needed to remove the bicycle. This suggests that the number of bicycle racks that could be created per parking space lies somewhere between 8 and 9.3.

Update 3 July 2016 - The city of Nijmegen reckons it can fit as many as 10 bicycle racks on a parking space.
Update 31 January 2017 - And the city of New York needs about nine parking spaces to accomodate 69 city bikes.
And a follow-up (in Dutch).

Web scrapping

Search volume for web scrapping and web scraping according to Google Trends (52-week moving average).

Search volume for web scrapping as percentage of volume for both terms, according to Google Trends (52-week moving average).

I came across the following quote on the Web Scraping website:

I searched my email and found over the last few years I received 76 messages from clients containing the text Web Scrapping rather than the usual spelling Web Scraping. And this is not unique to my clients - currently Google has 122,000 results for “Web Scrapping” compared to 447,000 results for “Web Scraping” - the correct spelling returns only 4x the number of results. So in light of this common spelling mistake I registered the domain and redirected it here.

I thought this had to be a joke - but it wasn’t. The domain redirect actually works, and there does appear to be a persistent search volume for web scrapping, even if its share of total web scra[p]{1,2}ing searches has declined considerably.


The moralism and hypocrisy around ad blockers

With my new iPhone, I can finally install ad blockers. When I tried to find information about the available options, I was struck by the moralism and hypocrisy of many articles on the subject. This subtitle says it all: How to use ad-blockers in iOS 9 (and why you shouldn’t).

Sure, the article makes some valid points. One may question Apple’s motives for allowing ad blockers. And certainly, one may question Adblock’s policy to allow «acceptable ads» from companies that pay them a fee (so use an alternative like the open source uBlock Origin instead). But the claim that ad blocking could «kill journalism as we know it» seems a bit over the top.

The advertising industry tries to frame ad blocking as an attack on «the little guy», by which they mean small, independent publishers. Their strategy is similar to the Home taping is killing music campaign of the 1980s, by which the music industry tried to make us believe that home taping was bad for musicians. In reality, home taping was killing the profits of the very industry that was exploiting those musicians in the first place.

Journalists should be paid for their work, but I’m not convinced advertising is the solution. Ads are annoying, they slow down the internet, they waste valuable surface on mobile screens, they often come with scripts that track you and sometimes they spread malware. Perhaps even more importantly: ideally, journalists shouldn’t depend on advertising in the first place, because advertising is killing independent journalism.

So how should journalists get paid? I’m not sure there’s an easy answer. One way is to pay collectively, which may work rather well (BBC), but it does entail some degree of state regulation. Another way is to buy subscriptions from each site or publisher who publish interesting articles - but that’s rather cumbersome.

A practical alternative are subscription services like Blendle - described as the «the Netflix or Spotify for journalism» (although it’s more like iTunes in that you pay per article). Blendle is an interesting initiative, but there’s reason for caution.

If successful, services like Blendle may well develop into large corporations that try to control access to news stories - much like Spotify tries to control access to music (and Facebook tries to control access to news stories). The outcome could be that subscription services become profitable by exploiting journalists. Also, subscription services could amass an unhealthy degree of control over what we read, and could introduce similar opaque algorithms as the ones Facebook uses to decide what content we get to see.

Things might get interesting if journalists would draw inspiration from musicians and set up cooperatives. These could take the form of not-for-profit Blendle alternatives that offer independent quality journalism at a fair price, produced by journalists who are paid a fair wage for their work.

For now, ad blockers not only offer practical benefits; they also force the internet to address its unhealthy dependency on advertising.


Twitter discovers Steven Kruijswijk

Tweets mentioning names of riders, as percentage of all tweets with hashtag #giro, per day (smoothing applied). Data updated every hour (to update chart, clear browers history or click here to view the chart). Chart:

If all goes well, Steven Kruijswijk might just be the first Dutch rider in ages to conquer the podium in a large race, journalist Thijs Zonneveld wrote on Friday 20 May. At that point, Twitter hadn’t really discovered Kruijswijk yet. That changed on Saturday, when Kruijswijk won the pink jersey.


Strava wants my commute data

Dutch tv recently aired a fascinating documentary on the «smart city» phenomenon. Companies like Google are teaming up with local governments to further expand their already huge datasets on human behaviour, raising the spectre of total control and absence of privacy (someone used the word panoptical).

Proponents claim the smart city will make cities more efficient and perhaps even sustainable. But judging by the examples given by Amsterdam’s smart city czar (he was quoted in the same documentary), the main beneficients may well be motorists. Big data is used to help them navigate their car through the city and find a place to park it. In fact, only one out of Amsterdam’s ~100 smart city projects even mentions the word fiets (bicycle).

And now Strava wants my commute data. They’ve proclaimed tomorrow, the 10th of May, Bike to Work Day. If you’ll upload your ride to work, they promise to make your commutes count:

With data like this, cities can better understand how people choose to interact with the network of roads, bike paths and intersections. The result is improved decision-making, smarter planning, safer streets and more people biking, running and walking. Better data is a catalyst for change.

Bringing a bit more balance to the smart city phenomenon by adding lots of cycling data sounds like a good idea. But will it work? When a very similar initiative was run by Dutch cyclists’ organisation Fietsersbond, Bicycle Count Week, a critic argued that some of the worst bicycle infrastructure in Amsterdam can easily be identified without recording any rides. These problems remain unsolved not for lack of data, but for lack of political will.

Personally, I’d argue that data can be useful, if used critically. But I’m not sure the interpretation of data should be left to the smart city alliance of local governments and corporations.

So will I upload my ride to work tomorrow? To be honest, I’ll probably forget to record it in the first place.

The smart city documentary, part of VPRO’s Tegenlicht series, can be seen in Dutch here. The VPRO has translated some of its Tegenlicht (Backlight) documentaries, but I don’t think this one is available in English yet.