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Record W2134927350 · doi:10.1177/0886109915580346

“Don’t Take the Social Out of Social Work”

2015· article· en· W2134927350 on OpenAlexaffabout
Marjorie Johnstone

Bibliographic record

VenueAffilia · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSocial workSociologyIdentity (music)Social WelfareFormative assessmentGender studiesState (computer science)FeminismSocial changePolitical sciencePublic administrationLawAestheticsPedagogy

Abstract

fetched live from OpenAlex

Through an historical biographical lens, this article examines the career of an early Canadian social worker, Bessie Touzel (1904–1997). Touzel was a socialist feminist and practiced a left-leaning form of social work during the formative years of the profession. This was in tension with the earlier dominant ideas based on an imperial Anglo-Christian worldview. Two world wars, the Great Depression, and the establishment of the welfare state in Canada are the backdrop to contested ideas on the identity of the newly establishing female-dominated profession. As a woman in senior administration in early public social services, Touzel was a feminist pioneer with a vision of equal rights within a framework of universal rights. A closer look at her career illuminates not only the obstacles and challenges she faced as she strove to defend her personal social work values but also highlights the debates, which the profession struggled to reconcile.

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)0.008
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.318
Threshold uncertainty score0.633

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0260.097
Scholarly communication0.0140.011
Open science0.0020.006
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0040.002

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 head0.100
GPT teacher head0.407
Teacher spread0.307 · 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
GenreCommentary

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

Citations3
Published2015
Admission routes2
Has abstractyes

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