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Record W4403601882 · doi:10.4000/12gy0

La cause animale par l’image. Presse illustrée et mouvement conservationniste britannique

2024· article· fr· W4403601882 on OpenAlexaff
Vincent Lavoie

Bibliographic record

VenueTransbordeur. · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsÉcole Nationale d'Administration PubliqueUniversité du Québec à Montréal
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Dès la première moitié du XXe siècle, le mouvement conservationniste britannique fait grand usage des images photographiques pour sensibiliser les populations, essentiellement occidentales, à la disparition de la faune en Afrique centrale et de l’Est, là où l’Empire exerce son emprise coloniale. Ce mouvement connaît dans les années 1960 d’importantes mutations tributaires de facteurs géopolitiques avec la fin de la colonisation, institutionnels avec la création d’organisations internationales de conservation de la faune (WWF) et médiatiques avec la production massive de reportages animaliers, tant pour la télévision (BBC, ITV) que pour la presse périodique illustrée. Plaque tournante des élites britanniques de la protection animale et environnementale, le mensuel Animals (1963-1983) offre un éclairage singulier sur cet écheveau de considérations politiques, relationnelles et iconographiques, cela à une époque où la photographie animalière est elle-même soumise à des usages contrastés (éthologiques, publicitaires, récréatifs, etc.), souvent au sein de ces publications soutenant la cause animale.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.084
Threshold uncertainty score0.232

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.004
Scholarly communication0.0070.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0690.008

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 head0.051
GPT teacher head0.319
Teacher spread0.268 · 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
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

Citations0
Published2024
Admission routes1
Has abstractyes

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