MétaCan
Menu
← Back to cohort
Record W4401740249 · doi:10.1515/9782760556676

Le caribou n'a plus le même goût

2024· book· fr· W4401740249 on OpenAlexaboutno aff
Esther Lévesque, José Gérin-Lajoie, Alain Cuerrier, Laura Siegwart Collier

Bibliographic record

VenuePresses de l'Université du Québec eBooks · 2024
Typebook
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

Les changements climatiques affectent le monde entier, mais sont jusqu’à quatre fois plus intenses dans l’Arctique. Quelles seront les conséquences du dégel du pergélisol, de la modification de patrons de migration et de l’arrivée de nouvelles espèces sur les environnements nordiques et sur le mode de vie de ceux qui y vivent ? Dans cet ouvrage, des aînés et des experts locaux issus de huit communautés de l’Arctique canadien partagent leurs observations sur les changements qui affectent leurs activités traditionnelles, le climat, les animaux et la végétation en mettant notamment l’accent sur les petits fruits. Thème central à l’origine de ce projet, l’écologie des petits fruits a également favorisé la rencontre des femmes qui traditionnellement récoltent les plantes et les petits fruits ; elles représentent d’ailleurs plus de la moitié des personnes interviewées dans le cadre de ce livre qui s’adresse principalement aux Nunavimmiut (habitants du Nunavik) et à toute personne curieuse d’en apprendre davantage sur les changements en cours dans le Nord. Accompagnée de synthèses des changements observés, de figures et de tableaux comparatifs, cette édition en français et en inuktitut (Nunavik) est richement illustrée et apporte un éclairage précieux et unique à la littérature scientifique sur les changements climatiques.

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)0.002
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.121
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.006
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.192
Teacher spread0.176 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuePresses de l'Université du Québec eBooks→Same topicFrench Urban and Social Studies→French-language works237,207→