Educational Research - the Ethics and Aesthetics of Statistics

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38 M. Depaepe combination. Moreover, Tan’s research functions as the mother, as it were, of all the samples that are regularly recovered in the subsequent studies. Thus, on the basis of data of respondents (from diverse studies and contexts), statements are made about previous generations (questions about educational levels and professions of the parents and grandparents). Consequently, the time span under research is considerably expanded. On the other hand, the principle of synchronicity in regard to questioning risks fading into the mist. This is partly the result of continuous interference of the present and the past. Ultimately, a whole range of statistical techniques and operations (ranging from parameter estimations, calculation of chi-squares and so on) are applied to these collections of data. I am too poor a statistician to judge the validity of all these operations. Nevertheless, as a historian of education, I do wonder about the degree to which any account was taken of the quasi-infinite combination possibilities of variables, during the ‘fabrication’ of the[se] statistics (Popkewitz & Lindblad, 2001). It is obvious here that, from the well-nigh infinite sample of possibilities used (and published?), only those that gave a significant answer to the policy-relevant question were used. The others (those that were not deemed significant) were simply left aside. In association with the – 19th-century history of statistics in Belgium (Bracke, 2008), this numerical material continues to provide the primary building blocks for a discourse that is eagerly taken over by politicians, journalists and social scientists. Rather than wanting to accuse authors of manipulation – there can be little doubt that their research has scientific integrity – it seems to me that an over-sophisticated technique is set loose on a shaky basic construction of data in all four studies. I have long sought after an image to capture this insight. First, I thought of the proverbial sledgehammer cracking a nut. On further consideration, I think that rather the inverse is the case. Perhaps, a better image would be of a hippopotamus being pushed under the lens of a high-powered microscope. One would be astonished to observe the same flaccid gray tissue everywhere on the amorphous mass. Over a long period of time the belly of its body would be swelling more than the head or the tail ...In order to see the richly shaded hues of the educational past, one need not try to reinvent the source material. Rather one might search for the material in university archives. There, on the basis of registration lists, real data about the social origin and amount of schooling of the parents are kept. Obviously the construction or reconstruction of such data series would require much time and labour. Therefore, case studies (preferably by a team) should be designed that would be selected on realistic chronological geographical grounds. The quantitative material generated would have to be enriched by qualitative sources (interviews, life histories, ego documents) for the same cases. Indeed, recalling Breidbach, one who wishes to understand the effects of the expansion of the universities in Flanders will have to look through and beyond the numbers. Notes 1. See also Hudson (2000, p. 211) who concludes as follows: ‘in order to create a new monumentum in economic history, it will be important for historians to avoid the mistakes of the past: carelessness with sources and with questioning the data, preoccupation with oversimplified
3 Dazzling Statistics? 39 neoclassical and macro-level theorising, anachronistic application of present-centered assumptions, [...]’. 2. See Groenez (2008, pp. 5, 14): OR = odds1 odds2 = π 1j/π 1j ′ π 2j /π 2j ′ 1 + π 1j Relatieve rekruteringskracht j − j ′ π 1j ′ = OR. 1 + π 2j π 2j ′ = n 1j n 1+ / n 1j ′ n 1+ n 2j n 2+ / n = n 1j · n 2j ′ 2j ′ n n 1j ′ · n 2j 2+ 1 + n∗ 1j n ∗ / n∗ 1j ′ 1+ n ∗ 1+ = OR. 1 + n∗ 2j n ∗ / n∗ 2j ′ 2+ n ∗ 2+ 1 + λ 1δ j n 1j Relatieve rekruteringskracht j − j ′ λ 1 δ j ′ n 1j = OR. 1 + λ 2δ jn 2j λ 2 δ j ′ n 2j 3. See Groenez (2008, p. 11): 1 + δ jn 1j δ j ′ n 1 j = OR. 1 + δjn 2j δ j ′ n 2 j 1 + n∗ 1j n ∗ 1j = OR. ′ 1 + n∗ 2j n ∗ 2j ′ Kans op diploma’s HSO en HO voor zonen van arbeiders en hogere bedienden Kans op diploma’s HSO en HO voor zonen van arbeiders en hogere bedienden HSO (arbeider) HSO (hoger bediende) HSO (arbeider) HSO (hoger bediende) 70% HO (arbeider) HO (hoger bediende) 80% HO (arbeider) HO (hoger bediende) 60% 70% 50% 60% 40% 50% 40% 30% 30% 20% 20% 10% 10% 0% 1911–1920 1921–1930 1931–1940 1941–1950 1951–1960 1961–1970 1971–1980 Evolutie van de odds (kansenverhouding P(HO)/P(HSO) en odds ratio arbeider (linkeras) odds ratio hoger bediende 10V arbeider (rechteras) Odds hoger bediende (linkeras) Odds ratio 2,5 0,0 0% 1911–1920 1921–1930 1931–1940 1941–1950 1951–1960 1961–1970 1971–1980 Evolutie van de odds (kansenverhouding P(HO)/P(HSO) en odds ratio arbeider (linkeras) odds ratio hoger bediende 10V arbeider (rechteras) Odds hoger bediende (linkeras) Odds ratio 2,5 0,0 Odds ratio=odds1/odds2 2,0 5,0 2,0 5,0 1,5 4,0 1,5 Odds ratio=odds1/odds2 4,0 odds1 3,0 3,0 1,0 1,0 2,0 odds1 2,0 0,5 1,0 0,5 1,0 odds2 odds2 0,0 1911–1920 1921–1930 1931–1940 1941–1950 1951–1960 1961–1970 1971–1980 0,0 0,0 1911–1920 1921–1930 1931–1940 1941–1950 1951–1960 1961–1970 1971–1980 0,0 100% recruteringsviver HO (arb) recruteringsviver HO (hog bed) recruteringskracht HO (arb) recruteringskracht HO (Hog bed) 100% recruteringsviver HO (arb) recruteringsviver HO (hog bed) recruteringskracht HO (arb) recruteringskracht HO (Hog bed) 90% 90% 80% 80% 70% 70% 60% 60% 50% 50% 40% 40% 30% 30% 20% 20% 10% 10% 0% 1911–1920 1921–1930 1931–1940 1941–1950 1951–1960 1961–1970 1971–1980 0% 1911–1920 1921–1930 1931–1940 1941–1950 1951–1960 1961–1970 1971–1980 Fig. 7: Constructie van de relatieve kansenverhouding HSO-HO, (mannen, links; vrouwen, rechts)
Page 2 and 3: Educational Research: The Ethics an
Page 4 and 5: Paul Smeyers · Marc Depaepe Editor
Page 6: Earlier Volumes in this Series Educ
Page 9: viii Contents 10 The Good, the Beau
Page 12 and 13: 2 P. Smeyers and M. Depaepe their a
Page 14 and 15: 4 P. Smeyers and M. Depaepe more fo
Page 16 and 17: 6 P. Smeyers and M. Depaepe The cha
Page 18 and 19: 8 P. Smeyers and M. Depaepe concern
Page 20 and 21: 10 P. Smeyers and M. Depaepe appear
Page 23 and 24: Chapter 2 The Lure of Statistics fo
Page 25 and 26: 2 The Lure of Statistics for Educat
Page 35: 2 The Lure of Statistics for Educat
Page 38 and 39: 28 M. Depaepe of the Leuven Catholi
Page 40 and 41: 30 M. Depaepe Tan’s final verdict
Page 42 and 43: 32 M. Depaepe of methodological bot
Page 44 and 45: 34 M. Depaepe tapping other sources
Page 46 and 47: 36 M. Depaepe In the context of dem
Page 50 and 51: 40 M. Depaepe 4. See Pelleriaux (19
Page 52 and 53: 42 M. Depaepe Schneider, J. (2010).
Page 54 and 55: 44 J.J.H. Dekker (see Section 4.4).
Page 56 and 57: 46 J.J.H. Dekker from their own par
Page 58 and 59: 48 J.J.H. Dekker a cohort study tha
Page 60 and 61: 50 J.J.H. Dekker child” (Van IJze
Page 62 and 63: 52 J.J.H. Dekker USA resulted in ev
Page 64 and 65: 54 J.J.H. Dekker of the problem”.
Page 66 and 67: 56 J.J.H. Dekker Dekker. J. J. H.,
Page 69 and 70: Chapter 5 Constructing Social Unity
Page 71 and 72: 5 Constructing Social Unity and Pre
Page 89 and 90: Chapter 6 n = 1: The Science and Ar
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6 n = 1: The Science and Art of the
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Chapter 7 To Frame the Unframable:
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7 To Frame the Unframable: Quantify
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Chapter 8 European Citizenship and
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8 European Citizenship and Evidence
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130 U. Stadler-Altmann and E. Keine
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146 J.P. Van Bendegem et al. quite
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148 J.P. Van Bendegem et al. expres
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150 J.P. Van Bendegem et al. This i
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152 J.P. Van Bendegem et al. A good
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154 J.P. Van Bendegem et al. Day wi
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156 J.P. Van Bendegem et al. statis
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158 J.P. Van Bendegem et al. 10.4 C
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160 J.P. Van Bendegem et al. Van Be
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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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