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Record W4236114441 · doi:10.24124/2008/bpgub528

The impact of personal injury motor vehicle incidents: the development of adverse stress reactions

2008· dissertation· en· W4236114441 on OpenAlexaff
Karen Laura Payton

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsPracticumIntervention (counseling)Health careWork (physics)Personal injuryNursingPsychologyPersonal careMedicinePublic relationsMedical educationPolitical scienceEngineeringFamily medicine

Abstract

fetched live from OpenAlex

As a result of primary health care reforms, the profession of social work has been afforded the opportunity to engage with individuals and families in various primary health care settings, including local hospitals. Social work professionals perform a range of distinct and important roles when working in hospitals. This is particularly evident when engaging in social work practice in the emergency room and intensive care unit. Crisis intervention represents merely one role that social workers must undertake in the emergency room and intensive care unit. However, this role is of importance, especially when working with individuals involved in personal injury motor vehicle incidents. This practicum report will briefly discuss the impact of primary health care reforms on the profession of social work and the roles that social workers engage in when working in primary health care settings. There will also be a brief discussion focusing on crisis intervention and personal injury motor vehicle incidents. This report will also briefly examine the practical experience of a Master of Social Work student working in a primary health care setting and the research completed focusing on personal injury motor vehicle incidents and the development of adverse stress reactions. --P.ii.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.424
Teacher spread0.368 · 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 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

Citations0
Published2008
Admission routes1
Has abstractyes

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