HUMAN FACTORS TOOL USE AMONG SWEDISH ERGONOMISTS
Bibliographic record
Abstract
This paper reports on a preliminary analysis of interviews conducted with Swedish ergonomists (SE). The study is using the theme of ‘tools’ to explore how ergonomists work on a daily basis. It was found that SEs often practice ergonomics as part of a ‘treatment’ process. Most SEs use their professional judgement when assessing and complement this with checklists, pictures and questionnaires. More sophisticated quantitative tools are less used. SEs who are internal employees, rather than external service providers, seem to be more able to participate in new design activities and to engage in follow-up on changes. SE’s ‘patient’ focus may pose a challenge to participating in design processes where stakeholders tend to have a ‘systems’ focus. This research is currently being extended to include Canadian ergonomists as well as industrial engineers in both countries.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".