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Exploring Positivism in Research Methods: Insights and Debates

Unveil the roots, principles, and impact of the positivist paradigm on research methods, from Comte to Popper. Dive into logical positivism, scientific naturalism, and critical perspectives. Understand how positivism shapes theory development and the pursuit of truth.

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Exploring Positivism in Research Methods: Insights and Debates

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  1. Research Methods Positivism and its variants

  2. Why study Positivism? • Hughes & Sharrock (1997: 24): positivism was ≈ orthodoxy in social science • No longer believed? (Williams, 1976) • Yet economics still heavily influenced • Authors defined in terms of positivism • Positivist tools (e.g. survey) still dominate • Must try to give it a fair hearing!

  3. Roots of positivism • Renaissance/Enlightenment thought of 16th/17th Centuries • Philosophy divided into empiricism/ rationalism: foundation of knowledge experience/reason; Bacon/Descartes • Saint-Simon: liberate people from dominant ideas; French Revolution • Get past illusions to “social facts” (Durkheim)

  4. Comte’s positivism • Influenced by Hume’s attacks on metaphysics • Two bona-fide forms of knowledge: empirical and logical, but empirical emphasised • Precision, clarity and certainty • View world as machine (reflects Descartes) • World comprises deterministic laws, regularities; waiting to be discovered by the scientist

  5. Positivism: basics • Laws: whenever A, then B (plus CP) • Causality: constant conjunctions of events (Hume) • Single cause leads to single effect (Durkheim) • Mill’s tendency statements, Hume’s caution both too weak for modern positivists

  6. Scientistic naturalism • Social science should imitate natural sciences (although why? Never stated!) • Aim for “unity of method” • Differences acknowledged between subject matters • Science proceeds via observation, modelling, to get to laws

  7. Observation • “Brute facts” (not affected by any judgement): mimic natural sciences (e.g. atom, velocity) • Observation is preconception free (Durkheim) and Value-free (positive analysis) • Correspondence theory of truth • Variables; measuring properties present in entities • Quantification: counting frequency of some property present in some entity • Operationalism: object defined in terms of the means of measuring/checking it (Hausman: 14)

  8. Theory development • Individualism; reductionism • Modelling • Testing predictions of models • Verification • H-D model tries to solve problem of induction

  9. Logical positivism • Carnap, Mach (Vienna Circle), Ayer, Russell: trying to make positivism more logical • Meaningful (True) statements must be verifiable • But now analytic statements can be true by virtue of the logical rules by which they are deduced • Yet LP questioned ‘ideal types’

  10. Popper’s intervention • Karl Popper: capturing spirit of positivism in many ways but opposite in others • Sceptic: verification impossible • No theory proven; yet to be falsified • “Scientific” theories are testable • Theories set up bold conjectures to be tested • Test theories by their predictions

  11. Popper’s intervention • Falsification from a single counterexample • Learning by trial and error • Idealised view of science • Kuhn, Lakatos: Popper underestimated tenacity with which “failed” theories are retained • Kuhn: sciences proceed irrationally; normal vs. revolutionary science

  12. Friedman (1953) • Highly influential essay • Can be interpreted as combining elements of positivism with Popper • “positive economics” • Purpose of theory = prediction • Good theories predict well • Simplicity and precision also good

  13. Friedman • Assumptions of theories not important • Assumptions are always simplifications - cannot be “realistic” - cannot assess theory via “realisticness” • Assumptions are shorthand for conditions, etc. under which theory works • Model works “as if” assumptions are correct: e.g. mobile leaves; profit maximisation

  14. Conclusions • Positivism has had several highly significant effects on economics: • Mimic natural sciences • “Value-free” analysis • Causal laws: “if X then Y” type • Quantification • Tools used • Emphasis on deductive logic

  15. Conclusions • H-D model • Friedman also very influential • Assertions about “positive” economics, the role of assumptions, prediction and falsification (echoing Popper) adopted strongly (at least “officially”) • Both subject to considerable criticism • Next two lectures will engage criticisms of positivism and its variants

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