Vibrations, exiguïté, faible marge de manoeuvre : comment améliorer le poste de conduite du métro de Montréal? Une démarche concertée et ancrée sur la réalité des situations de travail
Bibliographic record
Abstract
Click here for the English version of this report_x000D_ Considérant les inconforts rapportés par les opérateurs, la STM et le syndicat des opérateurs de métro se sont unis pour demander à l'IRSST de mesurer les vibrations auxquelles étaient exposés les opérateurs et de recommander un nouveau siège pour la loge de conduite. Cette publication relate l'étude en trois volets (étude ergonomique, étude vibratoire et conception d'un prototype de siège), s'appuyant sur une série de simulations, de tests et d'essais et menant à l'implantation de nouveaux sièges et de modifications à la loge de conduite. Le document illustre également comment la mise en place d'un groupe de travail et d'un comité de suivi, engageant la participation paritaire de tous les acteurs concernés, des chercheurs et d'un consultant, a facilité le processus._x000D_ Abstract_x000D_ In view of the discomforts reported by Montréal's subway operators, the STM and the union representing subway operators joined forces to ask the IRSST to quantify the level of vibrations to which the operators were exposed and make recommendations concerning a new seat for the operator cab. The summary document describes the three-part study (ergonomic study, vibration study, and design of a seat prototype), which involved a series of simulations and laboratory and actual-cab tests, and ultimately led to both the installation of new seats and modifications to the operator cab. It also illustrates how the process was facilitated by the formation of a working group and steering committee involving the joint representation and active participation of all stakeholders concerned, as well as researchers and a consultant.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 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; 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".