Examining wildland fire fighter candidate pass rates over five years post-implementation on a newly-developed physical employment standard1
Bibliographic record
Abstract
BACKGROUND: To assess the post-implementation impact of the Canadian Type 1 Wildland Fire Fighter (WFF) Fitness Test Circuit (WFX-FIT), a retrospective descriptive analysis of anonymized aggregate data collected between 2012-2016 was conducted. OBJECTIVES: The objectives were to examine the pass rates of Type 1 WFF in each fire jurisdiction and on the standard for exchanging Type 1 WFF between agencies, the interagency exchange standard, by age group and sex and to propose what other information could be of value in assessing the effectiveness of implementing a physical employment standard. METHODS: Frequencies and pass rate percentages were compared by sex and age groups (<40 years, ≥40 years). RESULTS: Between 2012-2016, pass rates for all participants on the jurisdictional and interagency exchange performance standards improved from 93.2% to 95.6% and 79.1% to 87.6%, respectively. CONCLUSIONS: We conclude that since the WFX-FIT was implemented, there has been an increase in the number of exchange-eligible Type 1 WFF for suppression of wildfires in Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".