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Record W2029099632 · doi:10.1177/0735275113489806

Thinking about Food and Sex

2013· article· en· W2029099632 on OpenAlexaff
Vanina Leschziner, Adam Isaiah Green

Bibliographic record

VenueSociological Theory · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCognitionDeliberationInstrumentalismAction (physics)PsychologyField (mathematics)EpistemologyAutomaticityRational analysisProcess (computing)Cognitive psychologyCognitive scienceSocial psychologyPoliticsComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Overemphasizing automatic, dispositional cognitive processes, research on social fields has tended to undertheorize the active, reflective dimensions of cognition that shape practice. This has occurred, at least in part, as a reaction to the overly instrumentalist premises of rational action theory. But redressing the errors of an excessively instrumentalist notion of action by overemphasizing the automatic nature of cognition leaves us with a similarly inadequate understanding of how cognition works to influence practice in a field and, as a consequence, the ways in which change may occur from pressures originating within the field itself. In this article, we draw from data on cognition and practice in two kinds of fields—a sexual and a culinary field—to demonstrate how inherent structural pressures encourage instances of deliberate nondispositional cognition and practice. These data suggest an expanded model of practice in field theory that moves beyond a dual-process model of cognition and toward a more nuanced understanding of the relationship of automaticity and deliberation, and habituality and nonhabituality, in the routine practices of a field.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.010
Scholarly communication0.0040.005
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.029
GPT teacher head0.291
Teacher spread0.262 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations104
Published2013
Admission routes1
Has abstractyes

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