Data and phenomena

  title={Data and phenomena},
  author={Jim Woodward},
My aim in this paper is to draw attention to a distinction and to a related set of procedures which are important to understanding science but which, until very recently, have been neglected or misdescribed by philosophers of science. The distinction in question is the distinction between data and phenomena and the procedures have to do with inferring claims about phenomena from claims about data. I shall begin with a general characterization of what I mean by data and phenomena. I shall then… 

Detecting psychological phenomena: taking bottom-up research seriously.

  • B. Haig
  • Psychology
    The American journal of psychology
  • 2013
This article provides a methodologically informative account of phenomena detection with reference to psychology by presenting the important distinctions between data, phenomena, and theory and identifies a number of different methodological strategies that are used to identify empirical phenomena.

The Science of the Struggle for Existence: Theories, Models, and Explanatory Tools

INTRODUCTION This chapter begins with a confession. I have, to this point, been taking advantage of the ambiguity of the term theoretical , using it to describe what we can now see to be two quite

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Understanding Replication in a Way That Is True to Science

  • B. Haig
  • Biology
    Review of General Psychology
  • 2020
It is maintained that viewing replication as just one element of the wide array of scientific endeavors leads to the conclusion that it is not as prominent in science as is often claimed.

What exactly is stabilized when phenomena are stabilized?

This paper develops an analysis of the stabilization of phenomena that integrates two aspects that have largely been treated separately in the literature: one concerns the skills required for empirical work; the other concerns the strategies by which claims about phenomena are validated.

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It is argued that attempting to explain a phenomenon may provide reason to suspend judgment about its characterization, but this cannot provide warrant to recharacterize it if researchers cannot infer a phenomenon’s characteristics from this explanation.

The Functional Complexity of Scientific Evidence

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This article proposes a reconsideration of the view that, in order to better grasp the objects they study, qualitative researchers should bracket their preconceived ideas, particularly their

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Scientists and philosophers use the terms “theory”, “model” and “phenomena” in such a variety of ways that it may seem pointless to try to regiment these uses into some more definite structure. At

Bogen and Woodward’s data-phenomena distinction, forms of theory-ladenness, and the reliability of data

It is argued that both TLI and TLA are much stronger senses of theory-ladenness than the classical thesis and that neither TLI nor TLA can be accommodated within Bogen and Woodward’s account.



Saving the phenomena

A according to a widely shared view of science, scientific theories predict and explain facts about "observables": objects and properties which can be perceived by the senses, sometimes augmented by

Confirmation, Disconfirmation, and Informa-tion in Hypothesis Testing

Strategies for hypothesis testing in scientific investigation and everyday reasoning have interested both psychologists and philosophers. A number of these scholars stress the importance of

The Structure of Scientific Revolutions

A good book may have the power to change the way we see the world, but a great book actually becomes part of our daily consciousness, pervading our thinking to the point that we take it for granted,

Cartwright, Causality, and Coincidence

  • D. Mayo
  • Philosophy
    PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association
  • 1986
Cartwright argues for being a realist about theoretical entities but non-realist about theoretical laws. Her reason is that while the former involves causal explanation, the latter involves

Book Review:Data, Instruments, and Theory: A Dialectical Approach to Understanding Science Robert John Ackermann

One of the books you can enjoy now is data instruments and theory a dialectical approach to understanding science here.

Explanatory Unification

This chapter discusses the systematization capacity and the empirical content of the pattern or theory with respect to explanations, and can specify these parameters more precisely within the framework of the structuralist view of theories.

Confirmation Bias in a Simulated Research Environment: An Experimental Study of Scientific Inference

Numerous authors (e.g., Popper, 1959) argue that scientists should try to falsify rather than confirm theories. However, recent empirical work (Wason and Johnson-Laird, 1972) suggests the existence

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The Seven Sexes: A Study in the Sociology of a Phenomenon, or the Replication of Experiments in Physics

The replication of scientific experiments is discussed stressing the problem of communication between the originator of an experiment and a scientist intending to replicate it. Models of

The scientific imagination: case studies

[ANTONIO] ALIOTTA, The idealistic reaction against science, [facsimile of 1914 ed.], New York, Arno Press, 1976, 8vo, pp. xxii, 483, $28.00 JOHN R. BAKER, Thefreedom ofscience, [facsimiles of The