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Record W4390985429 · doi:10.1177/0032258x241228180

Understanding the physical fitness standard, recruitment, and retention of Canadian Emergency Response Teams

2024· article· en· W4390985429 on OpenAlex
Zachary Towns, Rosemary Ricciardelli, Kevin Cyr

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Police Journal Theory Practice and Principles · 2024
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsRoyal Canadian Mounted PoliceMemorial University of Newfoundland
Fundersnot available
KeywordsPhysical fitnessService (business)Physical securityPsychologyApplied psychologyComputer securityEngineeringBusinessComputer scienceMarketingMedicine

Abstract

fetched live from OpenAlex

Canadian police services rely on their Emergency Response Teams (ERT) to respond to diverse calls for service, requiring ERT members to meet physical fitness standards aligned with the physically demanding components of ERT responsibilities. In the current article, we explore the different physical testing components of Canadian tactical teams to better understand the physical testing standards for ERT. We do this by investigating how members of the Association of Canadian Critical Incident Commanders respond to closed and open-ended survey items related to fitness testing for ERT members, consequences of not passing ERT physical testing standards, and how fitness standards are perceived as creating barriers to member retention and recruitment to ERT. We center our discussion on the need for a physically capable police service to ensure security, reduce risk, and enhance public safety and suggest potential avenues for policy changes tied to physical testing standards as ways forward.

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.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.352
GPT teacher head0.489
Teacher spread0.137 · 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