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Record W3130049306 · doi:10.1177/0020872821989799

Global standards for social work education and training

2021· article· en· W3130049306 on OpenAlexaff
Vasilios Ioakimidis, Dixon Sookraj

Bibliographic record

VenueInternational Social Work · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSocial workWork (physics)Product (mathematics)Public relationsPolitical scienceMedical educationSociologyPedagogyMedicineEngineeringLaw

Abstract

fetched live from OpenAlex

This is the final document adopted at the International Association of Schools of Social Work (IASSW) and the International Federation of Social Workers (IFSW) General Assemblies in 2020. The updated Global Standards for Social Work Education and Training is the product of an extensive global consultation that lasted for more than 18 months and included a wide range of social work academics, practitioners and experts by experience across 125 countries, represented by 5 regional associations and engaging with approximately 400 universities and further education organisations. The consultation and publication process was co-ordinated by Professor Vasilios Ioakimidis (IFSW) and Professor Dixon Sookraj (IASSW).

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)0.027
metaresearch head score (Gemma)0.038
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: Review · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.038
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.006
Science and technology studies0.0020.003
Scholarly communication0.0060.004
Open science0.0040.006
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0360.032

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 head0.055
GPT teacher head0.439
Teacher spread0.385 · 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
GenreReview

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

Citations71
Published2021
Admission routes1
Has abstractyes

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