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Record W3204079424 · doi:10.1177/0020872820976756

International field education: A case study of developing an anti-colonial group study program in Mexico

2021· article· en· W3204079424 on OpenAlexaff
Christine A. Walsh, Elyse Borlé, Liza Lorenzetti, Lauren Birks, Lorena Cerecero, Pedro Isnardo de la Cruz Lugardo

Bibliographic record

VenueInternational Social Work · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsField (mathematics)Group workWork (physics)SociologyColonialismExploratory researchPedagogyPublic relationsPolitical sciencePsychologySocial scienceEngineering

Abstract

fetched live from OpenAlex

International field education offers an exemplary means by which social work students can enhance cultural awareness and develop skills in working with diverse communities. This article describes an exploratory study using 14 key informant interviews to establish a social work group study program in Mexico. Findings illustrate how the incorporation of key academic and community-based stakeholders using an anticolonial/postcolonial framework in international field education can contribute to an enriched experience for all participants. Providing social work students with exposure to epistemologies and ontologies that may differ from the Western-dominated education are important in understanding the human experience in different contexts.

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)0.003
metaresearch head score (Gemma)0.004
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: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.005
Scholarly communication0.0030.002
Open science0.0020.006
Research integrity0.0020.003
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 head0.056
GPT teacher head0.454
Teacher spread0.398 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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