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Record W6907497214 · doi:10.25316/ir-15462

Building resilience in volunteer firefighters: Bridging the research to practice gap

2021· other· en· W6907497214 on OpenAlexfundno aff

Bibliographic record

VenueVIURRSpace (Vancouver Island University) · 2021
Typeother
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsnot available
FundersWorkSafeBCVancouver Island University
KeywordsVolunteerDisadvantagedMental healthBridging (networking)Psychological resilienceVolunteer work

Abstract

fetched live from OpenAlex

There are approximately 14,000 firefighters in British Columbia (BC); notably, over 10,000 are volunteers or paid-on-call. The volunteer fire rescue services (FRS) globally tend to be vastly under-resourced in terms of equipment, apparatus, and training yet the volunteer FRS are the life-blood of the majority of communities in BC. The FRS is considered a high-risk profession in relation to physical and psychological hazards faced by firefighters as part of their job. Volunteer FRS are challenged to maintain an engaged volunteer membership when the work of firefighters is unpredictable, risky, and takes time away from family, work, and other obligations. Given the multitude of ongoing stressors faced by firefighters, it has become evident that attention must be paid to the mental health of firefighters. However, when assets are scarce and require prioritizing, services to preserve healthy minds are often backgrounded to seemingly more critical choices of gear, equipment, and apparatus. Hence volunteer firefighters are often disadvantaged when it comes to information, education, and initiatives for mental health. The purpose of this research was to create, present, and evaluate the effectiveness of a resilience education programme for volunteer firefighters.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.063
GPT teacher head0.365
Teacher spread0.301 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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