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Social Work and Professional Representation

2024· book-chapter· en· W4403633922 on OpenAlexaffabout
Lilian Negura, Yannick Masse, Maude Lévesque, Sébastien Savard, Mélanie Bourque

Bibliographic record

VenueOxford University Press eBooks · 2024
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversité du Québec en OutaouaisUniversity of Ottawa
Fundersnot available
KeywordsRepresentation (politics)Social workWork (physics)SociologyEngineering ethicsComputer sciencePolitical scienceEngineeringMechanical engineeringLaw

Abstract

fetched live from OpenAlex

Abstract This chapter on social work and professional representation provides an overview of the history of social work in Canada and explores the complex tensions defining the professional identity of social workers today, in both institutional and community settings. The chapter deconstructs the lasting dynamics fostered by the ideologies of social service, from the Judeo-Christian values of charity work to the neoliberalism of today. It then discusses the core policies and principles informing contemporary Canadian social work, the difficulties that they engender, and the ways in which professionals have responded to internal and external occupational pressures. Power relations influencing the social work identity are discussed as they relate to both current practice and the broader establishment of the profession nationally. The chapter concludes by highlighting the means of resistance that have strengthened, and continue to strengthen, Canadian social 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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.642
Threshold uncertainty score0.721

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0100.024
Scholarly communication0.0100.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.062
GPT teacher head0.335
Teacher spread0.274 · 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
Published2024
Admission routes2
Has abstractyes

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