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Record W28325536 · doi:10.1016/j.jsxm.2017.02.008

Skills development and theorising practice in social work education

2006· article· en· W28325536 on OpenAlexfundno aff
Peter Ford, Brenda Johnston, Rosamond Mitchell

Bibliographic record

VenueThe Journal of Sexual Medicine · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsDocumentationFraming (construction)PedagogyCritical reflectionPsychologyEngineering ethicsSociologyComputer scienceEngineering

Abstract

fetched live from OpenAlex

This project analysed, for the first time, rich data recently collected relating to one course module in a social work degree programme: skills development and theorising practice. It evaluated the module within a principled theoretical framework, that of criticality development (critical action, critical self-reflection, critical thinking). It focused on the micro-analysis of developmental processes in classroom interactions, as well as the linkages between course outcomes and proposed key skill development as specified in the course documentation. The study illuminated the contributions and limitations of such a module to student critical development within the context of current social work education concerns, and will have implications for the debate on skills training in the new degree, by examining the detailed processes by which social work students develop interpersonal skills. The project's findings are directly applicable across social work education, and they should also be generalisable to other contexts, such as education for the health professions, because of the theoretical framing.

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)0.012
metaresearch head score (Gemma)0.019
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0030.007
Scholarly communication0.0060.003
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.024
GPT teacher head0.394
Teacher spread0.370 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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