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Record W3157060790 · doi:10.1080/10437797.2021.1885540

A Survey of Trauma Education in Social Work Programs in the United States and Canada

2021· article· en· W3157060790 on OpenAlexaboutno aff
Shamra Boel‐Studt, Matthew Vasquez, Karen A. Randolph, Taylor Dowdy-Hazlett

Bibliographic record

VenueJournal of Social Work Education · 2021
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationSocial workCurriculumInclusion (mineral)Medical educationWork (physics)PsychologyMedicinePedagogyPolitical scienceSocial psychologyEngineering

Abstract

fetched live from OpenAlex

In the past 2 decades, social work education has increasingly advocated for inclusion of trauma-related content in educational programming. Yet, to date, little is known about the current state of trauma education and training in social work programs. The aim of this study is to describe trauma education and training in accredited, North American social work programs. The data are from an online survey of 192 social work educators from 165 universities with accredited social work programs in the United States (n=151) and Canada (n=14). Participants were asked whether trauma-specific education is offered, and if so, to provide the formats used to deliver the content, the type of curriculum used, and evaluation efforts. Most programs (67.9%) reported integrating trauma education into existing courses, with 61.4% of BSW programs and 65.4% of MSW programs offering some form of trauma education. Results suggest that social work educators are recognizing the importance of including trauma education in their programming. However, more evaluation is needed to identify specific trauma content being presented.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score0.851

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.039
GPT teacher head0.333
Teacher spread0.294 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations7
Published2021
Admission routes1
Has abstractyes

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