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Record W4281751000 · doi:10.1080/01609513.2022.2083744

Group social intervention by social workers: Challenges and issues

2022· article· en· W4281751000 on OpenAlexaffabout
Carol Castro, Óscar Labra, Stéphane Grenier, Aline Dunoyer

Bibliographic record

VenueSocial Work With Groups · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsSocial workIntervention (counseling)Group workWork (physics)Social groupConfidentialityPsychologyQualitative researchSocial psychologyPublic relationsSociologyNursingMedicinePolitical scienceSocial sciencePedagogyEngineering

Abstract

fetched live from OpenAlex

Social work with groups is one of the social work intervention methods, and describes an approach directed at individuals, families, and communities. Most articles discussing this intervention method result from research conducted in larger urban centers. This research is based on the training and needs of social workers doing group work; specifically, qualitative research on social workers practising group intervention work in northern Quebec (Canada). The results indicate social workers’ satisfaction with training that simultaneously integrates practical work and group theory in a university setting. Group intervention work in rural areas has certain advantages over social work in large urban centers (sharing and understanding of a shared reality, breaking down isolation barriers), but social workers also have to face certain challenges specific to their region, such as confidentiality, a lack of public transit for users, and the lack of importance placed by the health network on this type of intervention work.

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)0.295
metaresearch head score (Gemma)0.242
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.295
Threshold uncertainty score0.869

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2950.242
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.004
Science and technology studies0.0110.016
Scholarly communication0.0090.017
Open science0.0130.010
Research integrity0.0110.006
Insufficient payload (model declined to judge)0.0110.002

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 head0.037
GPT teacher head0.340
Teacher spread0.303 · 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.

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

Citations4
Published2022
Admission routes2
Has abstractyes

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