Ethics, Enlightened Self-Interest, and the Corporate Responsibility to Respect Human Rights: A Critical Look at the Justificatory Foundations of the UN Framework
Bibliographic record
Abstract
ABSTRACT: Central to the United Nations Framework setting out the human rights responsibilities of corporations proposed by John Ruggie is the principle that corporations have a responsibility to respect human rights in their operations whether or not doing so is required by law and whether or not human rights laws are actively enforced. Ruggie proposes that corporations should respect this principle in their strategic management and day-to-day operations for reasons of corporate (enlightened) self-interest. This paper identifies this as a serious weakness and argues that identifying the responsibility to respect human rights as an explicitly ethical obligation to be respected for that reason would provide a much stronger justificatory foundation for respecting the principle seen from a corporate perspective, given that corporations are accountable to their shareholders for their deployment of the firm’s financial resources.
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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 | 0.027 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.077 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.012 | 0.014 |
| 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".