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Record W1834325025 · doi:10.31265/jcsw.v7i1.80

Exploring the Unique Features of a First Nations Graduate-Level Social Work Program

2012· article· en· W1834325025 on OpenAlexaboutno aff
Ralph Bodor, Carol Melnyk-Poliakiwski

Bibliographic record

VenueJournal of Comparative Social Work · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsCeremonyGeneral partnershipAccreditationCurriculumMedical educationIndigenousSocial workContext (archaeology)SociologyWork (physics)Program evaluationPsychologyPedagogyPolitical scienceMedicineEngineering

Abstract

fetched live from OpenAlex

Recently, a one-time cohort of graduate-level social work students completed a unique MSW program. The program was delivered in partnership between the Faculty of Social Work, University of Calgary and Blue Quills First Nations College and, of the twenty four graduates; twenty-one were of First Nations or Me´tis ancestry. The program honored traditional knowledge and ways of learning combined with a critical analysis of Western perspectives of social work knowledge. Strong fiscal resources enabled the program to establish a formal support network for the students and to support the development of Indigenous curriculum and programming that encouraged success for the students. The program was fundamentally different than urban on-campus programs while still maintaining graduate level accreditation requirements. This analysis of the program required the use of Indigenous Research Methodology to collect and create an understanding of the program. Instructors commented on the centered, empowered, balanced, and congruent students. The formal and informal, concrete and invisible supports to the students ensured the success of this program and this cohort of students. As one student commented, the program started in ceremony, ended in ceremony, and could not fail within the context ceremony.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.005
Science and technology studies0.0070.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.409
GPT teacher head0.458
Teacher spread0.049 · 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 teacher head, not a consensus.

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

Citations2
Published2012
Admission routes1
Has abstractyes

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