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Record W4225080036 · doi:10.5296/ijsw.v9i1.19129

The Shifting Landscape of International Practicum in Social Work Education

2022· article· en· W4225080036 on OpenAlexaffabout
Wasif Ali, Julie Drolet, Kamal Khatiwada, Emmanuel Chilanga, Mohammed Nurudeen Musah

Bibliographic record

VenueInternational Journal of Social Work · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPracticumTransformative learningInternational educationSocial workSociologyPedagogyField (mathematics)Public relationsPolitical scienceEngineering ethicsHigher educationEngineering

Abstract

fetched live from OpenAlex

International practicum, or international field placements, create opportunities for social work students to address global social challenges in an international setting and prepare for social work practice. The landscape of international practica in social work has evolved and shifted over the last two decades. This article reports on the findings of a literature review that was conducted to understand how international practicum has changed over time. The study established search criteria that led to the inclusion of 70 publications, 16 in the first decade (2000 to 2010) and 54 in the second decade (2011 to 2020) utilizing the web of Science and Social Work Abstracts, as well as specific searches conducted on the University of Calgary Library Database, EBSCO host, ProQuest, and Google Scholar. The results of the literature review show that there were fewer publications in the first decade and the emphasis was on understanding international practicum and field models. During the second decade, the published literature on international practicum tripled, focusing predominantly on developing new field education models, engaging in critical reflection and theory, and how to create successful field placements for students through preparation, teaching, and discussion. International practicum opportunities are critical to fostering transformative learning in social work students, and post-secondary institutions will need to re-establish international field education programs after the COVID-19 pandemic.

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)0.020
metaresearch head score (Gemma)0.026
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.026
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.013
Science and technology studies0.0040.013
Scholarly communication0.0180.013
Open science0.0010.009
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.026
GPT teacher head0.387
Teacher spread0.361 · 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

Citations3
Published2022
Admission routes2
Has abstractyes

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