Educational Research - the Ethics and Aesthetics of Statistics

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108 E. Hemelsoet Recognising the ‘will to power’ in the current love for numbers gives us sufficient reason to judge the estimation practices in the context of irregular migration. But, as mentioned earlier, that does not solve the problem at hand: what course of action is left for the policy maker? The question that remains concerns whether or not there are other ways to ‘understand’ the situation that can be distinguished apart from attempts to ‘grab’ it. A possible alternative may be to develop a problemoriented policy that works towards finding solutions to current problems. Some irregular migrants would then be liable to prosecution as a result of policy that fights smuggling, human trafficking, poverty, etc. Stretching this line of thought, some decisions might even be directed towards particular cultures, religious groups or ethnicities. One can for example think about discussions on the foundation of Muslim schools in Western European countries or initiatives to promote school participation for Roma people. Irregular migrants are then not approached from the perspective of their (illegal) residence status, but from events they have participated in or been victimised by, or from the ethnical, cultural or religious group they belong to. It is unclear whether or not this would deal with the problem. Even if this approach is adopted, numbers will be sought after to estimate the size of the problem. Whether we are talking about irregular migrants, smuggling, criminality, poverty, Muslims, Roma people or anything else, obtaining an idea of the scope of a social problem seems an indispensable element of ‘understanding’ that problem and gaining insight into it even if this is only so that policy makers can decide on how the limited means that are available should be distributed. The earlier critique of attempts to estimate irregular migrants provided evidence of the limited value of these numbers when trying to gain insight into the phenomenon. However, the pragmatics of policy making shows that this limited contribution to understanding irregular migration is better than no contribution at all and that the critique itself has limits too. Estimations make sense, even if their reliability is very low. Although they cannot deliver the profound insight into social problems that is required for a well-founded policy, they can serve as a steppingstone for further research. The ‘will to power’ may indeed be present in the attempts to frame social phenomena in numbers, but this does not explain the ‘love of numbers’ and the attractiveness of quantitative data. Every search for understanding, whether it be quantitative, qualitative or even philosophical, is expressing a will to power i.e. to gain control over a situation. What makes numbers so attractive then might be their transparency and unambiguous character. That takes us back to the second element of the conceptual critique, namely, the homogenisation of irregular migrants. Here, the proposed policy alternative may deliver added value. This alternative does not start from the dichotomy between regular and irregular people, between people with a legal and an illegal residence. It is important to recognise the diversity of problems irregular migrants are dealing with. Indeed the very concept of an ‘irregular migrant’ (or any alternative concept referring to this group of people) as an umbrella to homogenise the present diversity should be seen as problematic. This could be a starting point for a more just approach to the complexity of their everyday social practices.
7 To Frame the Unframable: Quantifying Irregular Migrants’ Presence 109 Appendix 1: Methods for Stock Estimates Approach Data sources Method Estimation technique Main idea of calculation Direct approaches Based on immigration enforcement data Based on administrative statistics Multiplier methods Simple Multiplier Estimation of total with a simple multiplier based on derived or estimated ratio of ‘dark field’ vs. ‘clear field’ Methods of self-identification Capture-recapture/ Repeated capture Estimation based on probabilistic function derived from multiple recaptures of individuals in sample Matching of registers Estimation based on implied non-registration in two or more individually matched registers Random effect mixed modelling approach Evidence based on regularisation data Using data on status adjustments over time Estimation using statistical regression model assuming comparable apprehension rates of legal/illegal residents with statistical adjustment for random effects Inferences on the size and composition of irregular migrant stock prior to regularisation from data on applications for and grants of regularisations Inferences derived from data on changes in residence status after a period of irregular residence Based on surveys Survey methods Direct survey methods Reconstruction of a "random sample" of regular and irregular migrants through a re-weighting of the probability of contacts Snowball sampling methods Estimation using chain referral methods to obtain a sample of persons not registered vs. persons registered
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Educational Research: The Ethics an
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Paul Smeyers · Marc Depaepe Editor
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Earlier Volumes in this Series Educ
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viii Contents 10 The Good, the Beau
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2 P. Smeyers and M. Depaepe their a
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4 P. Smeyers and M. Depaepe more fo
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6 P. Smeyers and M. Depaepe The cha
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8 P. Smeyers and M. Depaepe concern
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10 P. Smeyers and M. Depaepe appear
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Chapter 2 The Lure of Statistics fo
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2 The Lure of Statistics for Educat
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28 M. Depaepe of the Leuven Catholi
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30 M. Depaepe Tan’s final verdict
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32 M. Depaepe of methodological bot
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34 M. Depaepe tapping other sources
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36 M. Depaepe In the context of dem
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38 M. Depaepe combination. Moreover
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40 M. Depaepe 4. See Pelleriaux (19
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42 M. Depaepe Schneider, J. (2010).
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44 J.J.H. Dekker (see Section 4.4).
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46 J.J.H. Dekker from their own par
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48 J.J.H. Dekker a cohort study tha
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50 J.J.H. Dekker child” (Van IJze
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52 J.J.H. Dekker USA resulted in ev
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54 J.J.H. Dekker of the problem”.
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56 J.J.H. Dekker Dekker. J. J. H.,
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162 P. Smeyers to be told. Moreover
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164 P. Smeyers us’. It goes witho
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166 P. Smeyers at the basis of the
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168 P. Smeyers indeterminism, as we
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170 P. Smeyers are steps (a plan as
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172 P. Smeyers to the simple fact t
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174 P. Smeyers 6. The role of the a
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176 P. Smeyers conditions. It is in
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178 I. Munday etc. on a PowerPoint
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180 I. Munday To show how Derrida p
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182 I. Munday might talk of 20 bags
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184 I. Munday is unclear whether th
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186 I. Munday in numerals. This mig
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188 I. Munday We might also note th
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190 R. Smith ‘Statisticism’, on
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192 R. Smith identify, and twice in
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194 R. Smith of the final sentence
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196 R. Smith between admitting that
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198 R. Smith 7 www.equalitytrust.or
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200 R. Smith It is an interesting q
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202 R. Smith self-esteem, happiness
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204 R. Smith Reeves, R. (2009, Apri
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206 P. Standish Some students’ no
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208 P. Standish abstract ratio, wit
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210 P. Standish Rice $1.73 1 / 2 Mo
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212 P. Standish research none of us
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214 P. Standish of the products but
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216 About the Authors co-editor-in-
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218 About the Authors voor Wetensch
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220 Author Index Elkins, G. R., 190
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222 Author Index Silverman, J. G.,
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224 Subject Index I Inequality, 29-
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