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Record W4378384872 · doi:10.1515/9780773599741

Smitten by Giraffe

2016· book· en· W4378384872 on OpenAlexaboutno aff
Anne Innis Dagg

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2016
Typebook
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsZoologyBiology

Abstract

fetched live from OpenAlex

When Anne Innis saw her first giraffe at the age of three, she was smitten. She knew she had to learn more about this marvellous animal. Twenty years later, now a trained zoologist, she set off alone to Africa to study the behaviour of giraffe in the wild. Subsequently, Jane Goodall and Dian Fossey would be driven by a similar devotion to study the behaviour of wild apes. In Smitten by Giraffe the noted feminist reflects on her scientific work as well as the leading role she has played in numerous activist campaigns. On returning home to Canada, Anne married physicist Ian Dagg, had three children, published a number of scientific papers, taught at several local universities, and in 1967 earned her PhD in biology at the University of Waterloo. Dagg was continually frustrated in her efforts to secure a position as a tenured professor despite her many publications and exemplary teaching record. Finally she opted instead to pursue her research as an independent “citizen scientist,” while working part-time as an academic advisor. Dagg would spend many years fighting against the marginalization of women in the arts and sciences. Boldly documenting widespread sexism in universities while also discussing Dagg’s involvement with important zoological topics such as homosexuality, infanticide, sociobiology, and taxonomy, Smitten by Giraffe offers an inside perspective on the workings of scientific research and debate, the history of academia, and the rise of second-wave feminism. A new preface relates Dagg’s experience as the subject of the documentary The Woman Who Loves Giraffes .

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.089
Threshold uncertainty score0.298

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0080.002
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0890.037

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 head0.016
GPT teacher head0.245
Teacher spread0.229 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2016
Admission routes1
Has abstractyes

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