Protecting Third Party Business Interests Under Canadian Freedom of Information Legislation: A Review of British Columbia’s Act
Bibliographic record
Abstract
Applicants requesting access to a governmental record relating to the supply of goods and services (such as an outsourcing arrangement) will invariably expose third party business interests due to the nature of those contracted obligations. The burden rests with the third party to demonstrate that the information in question satisfies all three (3) limbs of the statutory provision – namely, that it was sensitive business information supplied in confidence that would result in a loss of competitiveness (whether in terms of negotiating leverage, or overall marketplace/economic competitiveness). It is the term ‘supplied’ that will receive the bulk of our attention in this article. We aim to show that the term has been interpreted and applied in an artificial, arcane and unreasonable manner by the Information and Privacy Commissioner. The focus of this article will be British Columbian law, primarily due to the sheer number of decisions – especially in relation to outsourcing arrangements – rendered by that Province’s Office of the Information and Privacy Commissioner.
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 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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.019 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".