TRANSPORT SÛR ET DURABLE : UNE NOUVELLE APPROCHE DES PARTIES PRENANTES POUR LE MANAGEMENT DU TSD Partie 2 : Le mode d‘emploi
Bibliographic record
Abstract
This communication aims to present an innovative reflection on the stakeholder theory and safe and sustainable transport (SST). In particular, it is to examine the significance of this recent approach for the management of SST system. This reflection is indeed the subject of increasing attention in managerial practices and lies at the heart of debates that address the problem of SST. It encompasses a set of proposals that suggest that all stakeholders should be put at the heart of SST in a partnership approach and collaboration. The article will introduce a new way of thinking about optimal governance, there by driving the SST strategy in a participatory and responsible logic. Among the deliverables to propose at the end of this article: Identify all stakeholders involved in the SST ; Presentation of the classification scale stakeholders in the SST ; Presentation of roles and responsibilities of STAKEHOLDER and their impact on road safety; Presentation of a battery SST actions in different places by different STAKEHOLDERS Exposure of an array of information and actions between the STAKEHOLDERS in the SST
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.022 | 0.016 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.015 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".