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18 Beyond Regression: The Need for Predictive Models

Rein Taagepera

Open publisher page 2 citations

Abstract

Abstract Society needs more from social sciences than they have delivered, and this book offers openings. To the society at large, quantitative social scientists presently seem no better at prediction than qualitative historians, philosophers, and journalists — they just look more boring. computers could be a boon to social sciences, but they have turned out a curse in disguise, by enabling people with insufficient understanding of scientific process to use canned computer programs and grind out reams of numbers parading as “results,” to be printed — and hardly ever used again. One may discard this book on the basis of errors of detail, but the problems it points out will still be there. Unless corrected, they will lead to a Ptolemaic dead end.

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What this paper is about

Abstract Society needs more from social sciences than they have delivered, and this book offers openings. To the society at large, quantitative social scientists presently seem no better at prediction than qualitative historians, philosophers, and journalists — they just look more boring. computers could be a boon to social sciences, but they have turned out a curse in disguise, by enabling people with insufficient understanding of scientific process to use canned computer programs and grind out reams of numbers parading as “results,” to be printed — and hardly ever used again. One may discard this book on the basis of errors of detail, but the problems it points out will still be there. Unless corrected, they will lead to a Ptolemaic dead end.

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Available abstract

Abstract Society needs more from social sciences than they have delivered, and this book offers openings. To the society at large, quantitative social scientists presently seem no better at prediction than qualitative historians, philosophers, and journalists — they just look more boring. computers could be a boon to social sciences, but they have turned out a curse in disguise, by enabling people with insufficient understanding of scientific process to use canned computer programs and grind out reams of numbers parading as “results,” to be printed — and hardly ever used again. One may discard this book on the basis of errors of detail, but the problems it points out will still be there. Unless corrected, they will lead to a Ptolemaic dead end.

Key concepts: Curse, Process (computing), Grind, Computer science, Data science, Sociology, Engineering, Mechanical engineering

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