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Introduction: Philosophy in and Philosophy of Cognitive Science, Part II

2009· article· en· W2082520935 on OpenAlex
Andrew Brook

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTopics in Cognitive Science · 2009
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsCarleton University
Fundersnot available
KeywordsCognitionPhilosophy of scienceEpistemologyCognitive scienceInterpretation (philosophy)Philosophy of biologyPhilosophy of mindSuspectPhilosophy of psychologyPsychologyPhilosophyMetaphysics

Abstract

fetched live from OpenAlex

In this second installment on the theme, Philosophy in and Philosophy of Cognitive Science, we have two papers, very different from one another and both very interesting, by William Bechtel and Pierre Jacob. In the first installment, the three authors all talked about the role of philosophical work in cognitive science. In contrast, in this installment, the two papers illustrate two ways in which this work is done. In the last installment we introduced a distinction between philosophy of cognitive science and philosophy in cognitive science. The former consists of philosophical reflections on cognitive science, whereas the latter consists of philosophical contributions to cognitive research. Bechtel’s paper is a good example of work of the former kind, and Jacob’s paper is a good example of work of the latter kind. Drawing on philosophical work on the nature of explanation in good science, Bechtel applies control theory, an important episode in the history of biochemistry, and an underexplored way of thinking about the relationship of mental function to brain function and structure to the specific situation of cognitive science and argues that we are in need of advances in all three areas. His paper is indeed the philosophy of science of cognitive science, just as he says. In contrast, Jacob in his paper does cognitive research. Specifically, his paper is a contribution to the cognitive neuroscience of mirror neurons. Accepting the data produced by experimental work on these neurons, he argues that the prevalent interpretation of these data is suspect. He then argues that a better interpretation, a rather surprising one, that the activity of mirror neurons is the result of concept-application, is available. Looking at Jacob’s paper as a whole and using the old Reichenbach/Popper distinction between the context of discovery and the context of justification, between generating hypotheses and testing them, the paper shows that much good work can be done on testing hypotheses and finding alternative hypotheses better supported by data without doing new experiments, without generating new data—and that researchers trained in philosophy can be very good at doing it. In short, these two papers are excellent illustrations of the two roles for philosophy in relation to cognitive science that we delineated in the first installment of this theme.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.712
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.065
GPT teacher head0.360
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it