Human Factors Analysis of Aircrew Operational Tasks in a Fixed-Wing Search and Rescue Aircraft Cargo Compartment (Analyse des facteurs humains lies aux taches operationnelles qui sont executees par les membres d'equipage dans la soute des avions de recherche et de sauvetage)
Bibliographic record
Abstract
Abstract : The Joint Operational Human Sciences Centre (JOHSC), at the request of Director Air Requirements (DAR), conducted a human factors analysis of aircrew operational tasks in a Fixed-Wing Search and Rescue (FWSAR) aircraft cargo compartment. The aim of this study was to provide guidance on minimum cargo compartment dimensions based on operational duties performed by Search and Rescue Technicians (SAR Techs). Specifically, it includes an analysis of the entire workspace envelope, to determine compartment length, width and height requirements. A secondary aim was to address concerns regarding future risk of musculoskeletal injury to SAR Techs working in the cargo compartment of a FWSAR aircraft. The full range of operational tasks performed by SAR Techs in the current FWSAR aircraft was observed at squadrons in Trenton, Ontario and Comox, British Columbia. Space critical aerial delivery tasks and four relevant types of equipment were selected for analysis, including postural and spinal load assessments of manual materials handling (MMH) and anthropometry based on current SAR Tech demographics. Potential risk of musculoskeletal injury to SAR Techs during operational tasks was evaluated. Results were used to provide guidance based on ergonomics principals, standards in the industry, and current operational FWSAR procedures. Relevant anthropometry, secular growth trends, personal protective equipment (PPE) and workspace dimensions were considered. Based on a 99th percentile SAR Tech male (BoSS XXI), a minimal cabin compartment height of 198.7 cm, or rounded up 200 cm, is recommended. However, this value does not account for any head room clearance required under turbulent conditions.
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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 | 0.000 | 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 | 0.000 |
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".