Bibliographic record
Abstract
In May 2019, I was proud to take on the challenge of serving as the Canadian Ombudsperson for Responsible Enterprise (CORE). The CORE is the first Canadian Ombud with a business and human rights mandate, and the only Ombud office mandated to hold Canadian garment, mining and oil/gas companies accountable for human rights abuses that have taken place outside of Canada as a result of their operations, including their supply chains. Prior to the CORE, from 2009 to 2014, Canada monitored the conduct of mining and oil and gas companies operating outside of Canada through the Office of the Extractive Sector Corporate Social Responsibility Counsellor. This office was embedded within the department of Global Affairs Canada (GAC). The CORE operates at arm’s length from GAC and the addition of garment companies to the CORE’s mandate was catalyzed by the 2013 Rana Plaza disaster in Bangladesh which highlighted Canada’s exposure in the area of Human Rights in this sector. Significantly, the CORE’s mandate1 also involves promoting the implementation of both the United Nations Guiding Principles on Business and Human Rights (UNGPs),2 and the Organisation for Economic Cooperation and Development (OECD) Guidelines for Multinational Enterprises.3
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 | 0.001 | 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 | 0.000 | 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) | 0.025 | 0.017 |
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; both teacher heads agree on what is shown here.
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".