Constraints to participation in Canadian forestry advisory committees: a gendered perspective
Bibliographic record
Abstract
Although the public advisory committee has become a very common tool for involving local people in forest management decisions, it does not necessarily broaden the base of public input and may simply replicate the challenges of access, representation, and capacity to participate that are found in wider society. As a category of social exclusion, this study explores why women are significantly underrepresented on forest management advisory committees in Canada and how these committees function as gendered units. Research involved 25 semistructured interviews with members (and former members) of two forest management advisory committees: Tembec in Manitoba and NewPage in Nova Scotia. The strongest evidence in our study suggests that these committees operate within male-dominated institutions and particular masculine norms that are simply taken for granted. Thus, social relations based on gender often go unacknowledged. Findings also showed that the lack of critical mass of women often limited the active participation of the small number of women involved in committee activities. Our empirical observations suggest that unless we attend to gender when involving communities in establishing strategies for forest management, we will reinforce gender disadvantage and exclusion and overrepresent industrial and utilitarian interests of forestry over other community and ecocentric values.
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 | 0.020 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.057 | 0.023 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".