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Record W4249804451 · doi:10.32920/ryerson.14643957.v1

Progressive change-makers or agents of Colonialism? Taking another look at the CASWE’s Standards for curriculum accreditation

2021· preprint· en· W4249804451 on OpenAlexaffabout
Ameena Ashley Ali

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsToronto Metropolitan UniversityCentre for Social InnovationUniversity of Waterloo
Fundersnot available
KeywordsAccreditationCurriculumColonialismOppressionNeoliberalism (international relations)Social workSociologyInstitutionalisationPolitical scienceSocial justiceSocial changePedagogyPublic relationsSocial scienceEngineering ethicsLawPoliticsEngineering

Abstract

fetched live from OpenAlex

This major research paper (MRP) examines how Schools of Social Work (SSW) in Canada reproduce social workers who participate in and perpetuate existing systems of oppression. Social workers either end up continuing to contribute to existing oppressive structures in society or working towards breaking down those structures; and an integral part in making that distinction is the education that they receive. This MRP focuses on critically analyzing the Canadian Association of Social Work Education (CASWE) standards for Masters of Social Work (MSW) curriculum accreditation through an anti-colonial and post colonialism framework with an understanding of the effects of neoliberalism. This critical analysis was conducted through critical discourse analysis to reveal how colonialism and neoliberalism permeate curriculum standards which ultimately shape social work practice today. Main findings indicate that the curriculum accreditation standards have underlying discourses related to professionalism, social justice, surveillance, institutionalization and the absence of race.

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)0.010
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.990
Threshold uncertainty score0.545

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0130.041
Scholarly communication0.0110.005
Open science0.0010.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.128
GPT teacher head0.465
Teacher spread0.337 · 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.

Study designQualitative
DomainEvaluation
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
Published2021
Admission routes2
Has abstractyes

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