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Record W7008076553

Autour du paddock : hippodrome de Trois-Rivières

2024· book· en· W7008076553 on OpenAlexaboutno aff

Bibliographic record

VenueE-Artexte (Artexte) · 2024
Typebook
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsPassionTributeHuman beingPhotographyPhotojournalismSemiotics
DOInot available

Abstract

fetched live from OpenAlex

"'Autour du Paddock' is a true, poetic, and human immersion into a little-known world—that of harness racing. This book is a visual tribute to those who work far from the spotlight, in a universe where passion meets reality. This artistic reportage unveils the daily lives of these devoted individuals—breeders, grooms, drivers—through all weather conditions, whether under bright skies or during grey, rainy days. Each image tells a story: one of labour, effort, deep connection with the horses, and a milieu where women are taking on an increasingly significant role. There are no spectacular finish-line shots here, but rather sincere and sometimes unexpected moments, captured with artistic sensitivity. "Autour du Paddock" reveals the truth of this world: weathered faces, precise gestures, and that unique bond between human and animal, seized in soft or striking light." -- Distributor's website

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.983
Threshold uncertainty score0.397

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1190.041

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 head0.017
GPT teacher head0.291
Teacher spread0.274 · 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 designQualitative
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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