Clothing and Equipment Fit Among Male and Female Canadian Armed Forces Members
Bibliographic record
Abstract
INTRODUCTION: The fit of military clothing and equipment is essential for the health and safety of military operators. Given the aim of increasing the proportion of women and the known biological and morphological differences between male and female soldiers, an understanding of fit across different items of kit is needed. The aim of this study was to quantify subjective fit ratings of 8 items of military clothing and equipment, including combat shirt, combat pants, rucksack, small pack, tactical vest, fragmentation vest, helmet, and ballistic eyewear as a function of relative stature and occupational group among male and female Canadian Armed Forces members. MATERIALS AND METHODS: An online survey was distributed to male and female Canadian Armed Forces members, where fit was reported by participants according to a 7-point Likert acceptability scale. Participants were binned into 1 of 6 (3 males, 3 females) standing stature categories based on percentiles in a male and female distribution that included (1) under 35th percentile stature, (2) 35th to 80th percentile stature, and (3) over 80th percentile stature. Additionally, participants were separated according to occupational group: Group A: Infantry, Combat Engineer, Artillery, Armored; group B: Signals, Medical Technician, Intelligence, Signals Intelligence/Cyber Ops; group C: Supply Technician, Weapons Technician, Vehicle Technician, Electronic-Optronic Technician, Ammunition Technician; other: Not in other groups, examples include: Financial Services Administrator, Cook. This study was approved by the Defence Research and Development Canada Human Research Ethics Committee under protocol 2019-048, Amendment 2. RESULTS: There were significant effects attributable to stature category and occupational group on the fit of equipment. Specifically, fit acceptability of the rucksack helmet, small pack, and tactical vest was significantly affected by occupational group. Differences between stature categories were detected in all items with the exception of the small pack. CONCLUSIONS: Military equipment fit has previously been shown to have implications for protection, performance, and mobility. The results of the investigation demonstrate different patterns of fit acceptability in male and female soldiers across items of clothing and equipment and may require different solutions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".