MétaCan
Menu
Back to cohort
Record W3201372498 · doi:10.7202/1079516ar

Relations familles et intervenants

2021· article· fr· W3201372498 on OpenAlexaffvenue
Amnon Jacob Suissa

Bibliographic record

VenueÉducation et francophonie · 2021
Typearticle
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

À partir d’une réflexion théorique et d’observations cliniques, cet article tente d’analyser certains enjeux sociaux et thérapeutiques dans un contexte d’intervention entre familles et thérapeutes. À cette fin, l’article emprunte une démarche d’analyse sociale critique en trois parties. La première partie effectue un survol des changements sociaux contemporains ayant eu un certain impact sur les dynamiques familiales. La deuxième partie touche la question de l’étiquetage sociofamilial des problèmes associés souvent à la déviance par les intervenants d’une part, et les conséquences de ces processus d’étiquetage sur les résultats de prise en charge, d’autre part. Comme alternatives à ces effets, les concepts de compétence, information pertinente, temps, chaos et processus sont suggérés afin de donner du pouvoir aux membres des familles et permettre aux intervenants de se sentir plus à l’aise avec les difficultés parfois chaotiques des familles. En troisième partie, un exemple de cas en toxicomanie illustre comment le processus de conception/étiquetage du phénomène de l’alcoolisme compris comme une maladie par la majorité des intervenants, et selon l’idéologie des Alcooliques Anonymes, produit des effets thérapeutiques et sociaux improductifs sur les dynamiques familiales, et en particulier sur le développement des enfants.

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)0.004
metaresearch head score (Gemma)0.009
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0080.009
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0140.001

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 head0.053
GPT teacher head0.405
Teacher spread0.352 · 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

Citations2
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueÉducation et francophonieSame topicAging, Elder Care, and Social IssuesFrench-language works237,207