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Record W4214909570 · doi:10.3917/rf.019.0115

La rencontre familles-professionnels au temps de la covid-19

2022· article· fr· W4214909570 on OpenAlexaff
Jean-Pierre Gagnier, Carl Lacharité

Bibliographic record

VenueRecherches familiales · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Policies and Family
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsHumanitiesCoronavirus disease 2019 (COVID-19)Political science2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)EthnologySociologyPhilosophyMedicine

Abstract

fetched live from OpenAlex

Dans le contexte de la crise sanitaire et sociale causée par la pandémie de la covid-19, comment la rencontre des familles avec les professionnels s’est-elle transformée ? Cette question sera abordée par la description des répercussions que l’accroissement du sentiment d’insécurité et l’imposition de mesures sanitaires entraînent, de manière parallèle, dans la vie des familles et dans la vie personnelle et le travail des professionnels. Le concept de rencontre est employé comme cadre d’analyse de ce qui se joue depuis le début de cette pandémie dans le lien entre les familles et les professionnels chargés de les aider, les soutenir et les accompagner. Cette analyse permet de dégager certains repères pour la pratique professionnelle qui non seulement sont pertinents à ce moment-ci, mais laissent entrevoir ce qui méritera d’être consolidé à la sortie de crise.

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)0.009
metaresearch head score (Gemma)0.013
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 score0.097
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.014
Scholarly communication0.0040.004
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.175
GPT teacher head0.424
Teacher spread0.249 · 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
Published2022
Admission routes1
Has abstractyes

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