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Record W4406110818 · doi:10.1080/17441692.2024.2445826

Mapping out a Canadian university’s trauma-informed landscape: A preliminary exploration

2025· article· en· W4406110818 on OpenAlexaffabout
Mélanie Letendre Jauniaux, Heather L. Lawford

Bibliographic record

VenueGlobal Public Health · 2025
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsBishop's University
Fundersnot available
KeywordsThematic analysisAgency (philosophy)Vulnerability (computing)HarmEmpowermentReflexivityMedicinePsychologyNursingMedical educationPublic relationsQualitative researchSociologyPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Adversity and trauma are commonly misunderstood human experiences affecting most individuals across post-secondary campuses. Depending on contextual factors, they can lead to lifelong challenges or growth. Without an adequate understanding, well-meaning individuals and organisations may unknowingly perpetuate harm. Trauma-informed approaches (TIAs) can help organisations prevent harm, promote empowerment, and enhance connection. Preliminary investigations are critical for the development of sustainable TIAs. This exploratory study investigated the attitudes, knowledge, and workplace culture concerning adversity and trauma at a small Canadian university with no existing TIA. The study involved two phases: first, preliminary consultations with ten community stakeholders and a review of relevant literature, and second, nine semi-structured interviews with staff and faculty, followed by reflexive thematic analysis of the data. Four key themes emerged: (1) limited trauma awareness on campus, highlighting a need for system-wide training and tools, (2) privilege and vulnerability, disparities in safety, flexibility and agency across university departments, (3) pockets of safety, academic culture and other barriers to change, (4) suggestions to address barriers, through trauma education, human-centric practices, and systemic collaboration. This study provides insight into the readiness, challenges, and recommendations for developing system-wide trauma awareness in a Canadian university.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.916
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.056
GPT teacher head0.317
Teacher spread0.262 · 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 designNot applicable
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
Published2025
Admission routes2
Has abstractyes

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