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Record W7161951348 · doi:10.82308/46581

The emergence of harm reduction in Canadian social work: scoping themes for practice

2019· dissertation· en· W7161951348 on OpenAlexaboutno aff
Tyson Kelsall

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsHarm reductionHarmSocial workRelation (database)Space (punctuation)Work (physics)

Abstract

fetched live from OpenAlex

This thesis contains two separate manuscripts linked by a common objective of unearthing a better understanding of how harm reduction is, and can be, applied effectively in practice by social workers in Canada. The first manuscript outlines the theoretical underpinnings of harm reduction’s emergence in Canada. It contrasts harm reduction with traditional social worker roles in responding to people who are ‘deviant,’ with a focus on people who use drugs. The paper offers an understanding of harm reduction as a space within the confinement of Susan Sontag’s ‘special worlds’ for ‘the sick’ and asks how social workers can utilize harm reduction in their practice. The second manuscript is a multi-disciplinary scoping review of academic literature that examines what has been published about harm reduction in relation to Canadian social work practice. The thesis ends with practice, policy, and research recommendations

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)0.083
metaresearch head score (Gemma)0.125
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.237
Threshold uncertainty score0.884

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0830.125
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0170.040
Science and technology studies0.0270.035
Scholarly communication0.0330.011
Open science0.0060.013
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0040.000

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 head0.058
GPT teacher head0.445
Teacher spread0.387 · 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
Published2019
Admission routes1
Has abstractyes

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