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Record W2137077791 · doi:10.1017/s0007087409990677

The problem of raccoon intelligence in behaviourist America

2009· article· en· W2137077791 on OpenAlexaff
Michael Pettit

Bibliographic record

VenueThe British Journal for the History of Science · 2009
Typearticle
Languageen
FieldPsychology
TopicAcademic and Historical Perspectives in Psychology
Canadian institutionsYork University
Fundersnot available
KeywordsCuriosityCriminologyAnimal behaviorRaccoon DogsPsychologyEnvironmental ethicsSociologySocial psychologyPhilosophyZoologyBiology

Abstract

fetched live from OpenAlex

Abstract Even during its heyday, American behaviourist psychology was repeatedly criticized for the lack of diversity in its experimental subjects, with its almost exclusive focus on rats and pigeons. This paper revisits this debate by examining the rise and fall of a once promising alternative laboratory animal and model of intelligence, the raccoon. During the first two decades of the twentieth century, psychological investigations of the raccoon existed on the borderlands between laboratory experimentation, natural history and pet-keeping. Moreover, its chief advocate, Lawrence W. Cole, inhabited the institutional and geographic borderlands of the discipline. This liminality ultimately worked against the raccoon's selection as a standardized model during the behaviourist era. The question of raccoon intelligence was also a prominent topic in the contemporaneous debates over the place of sentiment in popular nature writing. Although Cole and others argued that the raccoon provided unique opportunities to study mental attributes such as curiosity and attention, others accused the animal's advocates of sentimentalism, anthropomorphism and nature faking. The paper examines the making and unmaking of this hybrid scientific culture as the lives of experimenters and animals became entangled.

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.873
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.008
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.347
Teacher spread0.315 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations26
Published2009
Admission routes1
Has abstractyes

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