The Value of Mainstreaming Human Rights into Health Impact Assessment
Bibliographic record
Abstract
Health impact assessment (HIA) is increasingly being used to predict the health and social impacts of domestic and global laws, policies and programs. In a comprehensive review of HIA practice in 2012, the authors indicated that, given the diverse range of HIA practice, there is an immediate need to reconsider the governing values and standards for HIA implementation [1]. This article responds to this call for governing values and standards for HIA. It proposes that international human rights standards be integrated into HIA to provide a universal value system backed up by international and domestic laws and mechanisms of accountability. The idea of mainstreaming human rights into HIA is illustrated with the example of impact assessments that have been carried out to predict the potential effects of intellectual property rights in international trade agreements on the availability and affordability of medicines. The article concludes by recommending international human rights standards as a legal and ethical framework for HIA that will enhance the universal values of nondiscrimination, participation, transparency and accountability and bring legitimacy and coherence to HIA practice as well.
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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".