Our study on the discrimination of people with foreign-sounding names in housing market in Switzerland has been picked up by the press. The sunday tabloid SonntagsBlick run the story with many details. I was happy to see that the news report, as well as the press coverage that followed in other newspapers, was quite accurate.
I even ventured into the online comments, just curious to see what the self-select group of commenters had to say. A few offered their own experience of what we describe in the report: flats not being available when a person with a foreign name phones up, but still available when a person with a ‘native’ name phones up. Quite a few defended the right to discriminate and offered their own experience as landlords, hearsay, and stereotypes as justifications for what we would call statistical discrimination. (This kind of ‘evidence’ is also quite ‘funny’ in the sense that whether you had a good or bad experience with tenants from XYZ, there’s another commentator with the opposite experience.) I find this quite interesting, and we had similar reactions in a study on hiring discrimination: A substantial part of the population does not seem to understand that statistical discrimination is also discrimination. Quite interesting is that none of the comments I have seen picked up on the difference between having a ‘foreign-sounding’ name, and being a foreign citizen — the perception as ethnic groups. Our results hold irrespective of citizenship, so we show that some Swiss citizens are discriminated (too) because of their name.
Press coverage: SonntagsBlick, Tages-Anzeiger, Bluewin, Basler Zeitung, Nau.ch, 20 Minuten, Mieterverband
Auer, Daniel, Julie Lacroix, Didier Ruedin, and Eva Zschirnt. 2019. ‘Ethnische Diskriminierung auf dem Schweizer Wohnungsmarkt’. Grenchen: BWO.
Image: cc-by turkeychik
I know it’s 5 years old, but I still think this description of academia deserves a wider audience.
In this chapter, Binswanger (a critic of the current scientific process) explains how artificially staged competitions affect science and how they result in nonsense. An economist himself, Binswanger provides examples from his field and shows how impact factors and publication pressure reduce the quality of scientific publications. Some might know his work and arguments from his book ‘Sinnlose Wettbewerbe’.
Binswanger, Mathias. 2014. ‘Excellence by Nonsense: The Competition for Publications in Modern Science’. In Opening Science: The Evolving Guide on How the Internet Is Changing Research, Collaboration and Scholarly Publishing, edited by Sönke Bartling and Sascha Friesike, 49–72. New York: Springer. https://doi.org/10.1007/978-3-319-00026-8_3. [open access]
This is a reminder of the current call by the Swiss-Subsaharan Africa Migration (S-SAM) network. The deadline for submissions is 19 August 2018.
We aim to build and strengthen long-term partnerships between migration researchers in Subsaharan Africa and Switzerland, and we have just launched our first call for pilot studies and exchanges: https://www.unine.ch/sfm/home/formation/ssam.html
Key countries are: Cameroon, Ghana, Kenya, and Uganda, as well as Côte d’Ivoire, South Africa, and Tanzania. We fund small pilot studies and exchanges for late PhD and early postdoctoral researchers. The focus is on reasons and preparations to migrate, health, and student migration.
The NCCR on the move have released another set of three videos on common preconceptions. Great summaries of some of the work done at the NCCR on the move.
A colleague recently commented that he is confused where I stand with regard to the academic use of MIPEX data. Apparently I have been rather critical and quite enthusiastic about it. I guess this sums it up quite well. I’ve always been critical of the (historical) lack of a theoretical base for the indicators used, and the often uncritical use of the aggregate scores as indicators of ‘immigration policy’ in the literature. I’m enthusiastic about its coverage (compared to other indices), the effort to keep it up-to-date, and the availability of the detailed data.
A few years back, I verified that it is OK to use the MIPEX as a scale (as is often done), highlighting redundancy in the items and that such scales could be improved:
In the context of the SOM project, we have demonstrated that it is feasible to expand the MIPEX indicators back in time. We did so for 7 countries back to 1995. I refined these data by using the qualitative descriptions provided to identify the year of the change, giving year-on-year changes since 1995 for the 7 SOM countries. These data are experimental in that they rely on the documentation and not original research. If that’s not enough, Camilla and I have then created a complete time series of the MIPEX indicators in Switzerland since 1848. This showed that we definitely can go back in time, but also that quite a few of the things MIPEX measures were not regulated a century ago.
Even with the short time in the SOM data, these data are quite insightful:
Later I provided a different approach: re-assembling! The idea is generic and does not apply to the MIPEX alone: make use of the many indicators in the database, but use your own theory to pick and choose the ones you consider most appropriate (rather than be constrained by the presentation in the MIPEX publications). I have demonstrated that the MIPEX data can be used to closely approximate the Koopmans et al. data, but immediately cover a wider range of countries and observe changes over time. Now we can have theory and coverage!
And yes, we can apply these data to gain new insights, like the nature of the politicization of immigrant groups: