Evaluation of the assessment process for major projects: a case study of oil and gas pipelines in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Over the next several decades, oil and gas production in Canada is expected to increase to meet growing demand in the United States and the Asia Pacific Region. Currently, eight major pipeline projects are being proposed in Canada to transport increased oil and gas production to market. This paper reviews potential impacts of the pipeline projects and develops a methodology for evaluating the current regime for assessing and managing project impacts based on best practices criteria. The results of the evaluation show that only three of 14 best practices criteria are met. The most significant deficiencies are: lack of clear decision-making criteria and methods; absence of decision-making processes that contain a legal obligation to provide compensation to those negatively affected by a project and ensure project benefits are equitably distributed; and no provision for comparative evaluation of competing projects. This paper identifies improvements required in environmental assessment and planning processes.
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.
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 | 0.003 | 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 | 0.000 |
| 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 it