Disclosing Disclosure's Defects: Addressing Corporate Irresponsibility for Human Rights Impacts
Bibliographic record
Abstract
Although many people believe that the role of business is to maximize shareholder value, corporate executives and board members can no longer ignore their companies' human rights impacts on other stakeholders. Over the past four years, the role and responsibility of non-state actors such as multinationals has come under increased scrutiny. In 2011, the United Nations Human Rights Council unanimously endorsed the "UN Guiding Principles on Business and Human Rights," which outline the State duty to protect human rights, the corporate responsibility to respect human rights, and both the State and corporations' duties to provide remedies to parties. The Guiding Principles do not bind corporations, but dozens of countries, including the United States, are now working on National Action Plans to comply with their own duties, which include drafting regulations and incentives for companies. In 2014, the UN Human Rights Council passed a resolution to begin the process of developing a binding treaty on business and human rights. Separately, in an effort to address information asymmetries, lawmakers in the United States, Canada, Europe, and California have passed human rights disclosure legislation. Finally, dozens of stock exchanges have imposed either mandatory or voluntary non-financial disclosure requirements, in sync with the UN Principles. Despite various forms of disclosure mandates, these efforts do not work. The conflict lies within the flawed premise that, armed with specific information addressing human rights, consumers and investors will either reward "ethical" corporate behavior, or punish firms with poor human rights records. However, evidence shows that disclosures generally fail to change behavior because: (1) there are too many of them; (2) stakeholders suffer from disclosure overload; and (3) not enough consumers or investors penalize companies by boycotting 2015] Disclosing Disclosure's Defects 85 products or divesting. In this Article, I examine corporate social contract theory, normative business ethics, and the failure of stakeholders to utilize disclosures to punish those firms that breach the social contract. I propose that both stakeholders and companies view corporate actions through an ethical lens, and offer an eight factor test to provide guidance using current disclosures or stakeholder-specific inquiries. I conclude that disclosure for the sake of transparency, without more, will not lead to meaningful change regarding human rights impacts.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".