L'OIT et la responsabilisation extraterritoriale des états pour encadrer les activités des entreprises multinationales
Bibliographic record
Abstract
The present thesis is a logical outgrowth of the author's realization that rapid market globalization, spearheaded by faceless multinational corporations, is at the root of widespread abuse of the developing world's labour force. The situation clearly calls for corrective action in the form of a normative framework of effective regulations. Such a regulatory framework must needs to be enforced by a respected and dynamic international organization. Our research on this topic leads us to believe that the International Labour Organization (ILO) would be in an excellent position to supervise a proactive strategy of this kind, directly or indirectly, as it has the political clout and history to compel multinational corporations to respect their workers' most basic rights. In order to establish our case, we examine the legal questions at stake in this case study. In particular, we address the key attributes of multinational corporations, the issue of territorial sovereignty, the tripartite system, and the need for national legislation in any strategy involving workers' rights vis-a-vis multinational corporations. Next, we summarize the current level of accountability that multinational corporations have to their cross-border labour force. We then go on to discuss the ILO, the organization at the core of our reflections on multinational corporations' current (lack of) workplace accountability. Our research leads us to conclude that the ILO has not only the power to play that role, but also the duty to do so.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 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".