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Record W2130965604 · doi:10.1159/000348485

Innovating Innovation Rate and Its Relationship with Brains, Ecology and General Intelligence

2013· letter· en· W2130965604 on OpenAlex

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBrain Behavior and Evolution · 2013
Typeletter
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsMcGill University
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesRoyal SocietyNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsEcologyPsychologyNeuroscienceCognitive scienceBiology

Abstract

fetched live from OpenAlex

the ecology of intelligence, while Wyles et al. [1983] had proposed that innovations, especially when they were socially transmitted, might serve as behavioral drivers of evolution, using the famous example of tits opening milk bottles. Around 1994, I started wondering whether there could be many more cases of innovations besides milk bottle opening hidden in the ornithology literature, and whether these cases could provide a valid quantitative estimate of cognition. The publication of McGill Biology colleague Rob Peters’ influential book The Ecological Implications of Body Size [Peters, 1983] (currently 3,920 citations on Google Scholar) gave me a kind of ‘quantification envy’ that animal cognition could be as ‘operationalizable’ as body size and used in a similar manner in comparative analyses. Initially, the innovation project targeted taxonomic differences in socially acquired versus individually acquired innovations, predicting that, if the taxonomic distribution of the two modes of acquisition did not differ, this would be further support for the argument that social and individual learning are different sides of the same coin. The socially acquired category was soon dropped because too few cases were found in birds, but the data did show for the first time that a field-based quantitative measure of intelligence was positively correlated with relative forebrain size [Lefebvre et al., In 2002, the three of us were working together at McGill University, brought together by our shared interest in animal innovation. We had begun to discuss writing a review on the different aspects of our work on behavioral flexibility, which we felt strengthened and supported one another. An ideal opportunity arose when then editor Walt Wilczynski devoted a special issue of BBE to a symposium on ‘Ecology and the Central Nervous System’, organized by Luc-Alain Giraldeau at the 2002 International Society for Behavioral Ecology congress in Montreal. In the paper we were able to discuss and review a new operational measure of cognition, innovation rate. Using innovation rate and related measures of behavioral flexibility, we provided evidence for convergent cognitive evolution in birds and primates, and for behavioral flexibility having important ecological and evolutionary consequences. Broadly, our contributions can be separated into three themes, and we discuss the genesis of each in turn.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.052
GPT teacher head0.319
Teacher spread0.266 · 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