Is Spotlighting Enough? Environmental NGOs and the Commission for Environmental Cooperation
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
The initial questions of our survey questionnaire focused on whether ENGOs were familiar with the CEC, and if so, how frequently they followed the proceedings of the CEC Tables 1 and 2 clearly illustrate that a substantial majority of respondents were not familiar with the CEC (66.3%) and that only a small percentage of those who were aware of the CEC frequently followed its proceedings (18.5%).5 In short, our survey results indicate that the CEC has a long way to go gain the attention of most ENGOs in both Canada and the United States. A Canadian ENGO leader said, "It's a matter of resources: ENGOs do not have enough to be consistent players." An American ENGO head added, "It doesn't mean there's no interest in the CEC... but there are no resources to be engaged with it." An interesting comparative note from the results listed in Tables 1 and 2 is that while a larger percentage of Canadian ENGOs than United States ENGOs (40.5% to 28.3%) said they were familiar with the CEC, a much higher percentage of United States respondents than Canadian respondents who were familiar with the CEC (30.8% to 7.1%) said they "frequently" followed the proceedings of the CEC. Again, this finding may well be an illustration of the lack of resources available to Canadian ENGOs. Reflecting on this point, a Canadian ENGO member stated "ENGOs are too dependent on Environment Canada for funding... The ENGOs are often put in the position of pushing for governmental environmental initiatives against business and industry. Environment Canada can also use the ENGOs as a counterweight.
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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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