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Record W4405455893 · doi:10.1080/02615479.2024.2438262

Study tour reflections: revisiting curricula through an international lens

2024· article· en· W4405455893 on OpenAlexaffabout
Timothy A. Dueck, Rebecca J. Federau, Brooklyn P. Gordon, Kaylee H. Lovesy, Alexis C. Vilan

Bibliographic record

VenueSocial Work Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsCurriculumLens (geology)SociologyOptometryPedagogyMedical educationPsychologyPolitical scienceMedicineOpticsPhysics

Abstract

fetched live from OpenAlex

This article compiles Canadian social work students’ reflections of an Austrian study tour and its influence on how they now view, interpret, and analyze the curricula from previously completed undergraduate social work courses. Overall, the study tour appears to have re-animated previous course material and brought new insight into curricula already covered in classes. Of particular interest is the recurring theme of one notable aspect of the tour, a site visit to the former Mauthausen Concentration Camp, which surfaces as an important factor in reflections on numerous courses. Other social service agency visits in the host city invited the students to consider alternate theories in social work practice, building on the ones covered in completed curricula. Further, the students considered ways in which social workers can consider these new study-tour-informed insights and perspectives in everyday social service delivery on macro, mezzo, and micro levels. In sum, international study tours appear to not only notably influence future social work practice but also invite new critical thinking regarding previous learnings.

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)0.018
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 score0.393
Threshold uncertainty score0.781

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0250.020
Scholarly communication0.0140.004
Open science0.0020.010
Research integrity0.0020.010
Insufficient payload (model declined to judge)0.0100.001

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 head0.102
GPT teacher head0.476
Teacher spread0.374 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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