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Record W2784523670 · doi:10.1177/0008417417753374

Précis – Discours commémoratif Muriel Driver 2017 Possibilités en matière de bien-être: Le droit à la participation occupationnelle

2017· article· fr· W2784523670 on OpenAlexvenueaboutno aff
Karen Whalley Hammell

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2017
Typearticle
Languagefr
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Description. Le thème du Congrès 2017 de l’Association canadienne des ergothérapeutes a suscité des réflexions sur les différentes manières d’orienter l’avenir de notre profession. But. Ce discours commémoratif Muriel Driver examine comment nous pourrions façonner l’avenir de l’ergothérapie afin qu’elle devienne plus importante, plus pertinente et plus avantageuse pour la société. Questions clés. Comme la participation occupationnelle est essentielle au bien-être humain et comme le bien-être fait partie intégrante des droits de la personne, l’ergothérapie pourrait promouvoir le droit de toute personne de participer à des occupations qui contribuent positivement à son propre bien-être et à celui de sa communauté. Conséquences. L’importance de l’ergothérapie pour la société sera manifeste lorsque nous nous concentrerons sans ambiguïté sur le bien-être, lorsque nous déploierons nos efforts au-delà de l’amélioration des capacités des individus dont la vie est déjà touchée par la maladie, les blessures ou les handicaps et lorsque nous aborderons les différents moyens d’atteindre le bien-être par la participation occupationnelle de toutes les personnes dont les possibilités—les occasions de faire ce que leurs capacités leur permettent de faire—sont contraintes de manière inéquitable.

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)0.008
metaresearch head score (Gemma)0.047
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.949
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.047
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.007
Scholarly communication0.0090.007
Open science0.0020.009
Research integrity0.0100.024
Insufficient payload (model declined to judge)0.0190.012

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 head0.205
GPT teacher head0.495
Teacher spread0.291 · 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
GenreCommentary

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

Citations4
Published2017
Admission routes2
Has abstractyes

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