Forestry workers-- an endangered species : countermovement mobilization on the west coast of Vancouver Island
Bibliographic record
Abstract
Vancouver Island's old growth temperate rainforest has been the focal point in the conflict between environmentalists and forestry workers. While a substantial body of sociological literature exists on participants in the environmental movement (EM), there is a dearth of literature on participants in anti-environmentalist countermovements. Share Our Resources of Port Alberni (Share) is a countermovement organization that emerged to act as a voice for forestry workers and resource dependent communities and to counter the 'misinformation' being spread by environmentalists. The conflict over forestry and conservation is fuelled as environmentalists become the "other" against which Share members mobilize and construct their collective identity - an collective identity characterized by a core of pro-industry, pro-community and anti-environmental sentiments. This thesis addresses two research questions: First, what are the underlying differences between members of the two movements with respect to their socio-demographics, values, networks, and collective identities? Second, if certain factors are important in explaining identification with the EM, then what factors are important in explaining identification with Share. Using bivariate correlation analysis and multiple regression analysis, three sources of data are analyzed: self-administered questionnaires sent to both Share (N=129) and EM members (N=381); and a telephone survey of the general public of Port Alberni (N=100). My results show that Share respondents are predominantly older, working class men employed in the forest industry without a great deal of formal education. Share members more highly value anthropocentrism and are more politically conservative. Identification with the forest industry is the strongest and most significant predictor of identification with Share. The most theoretically interesting and surprising finding is that out-group ties or ties to environmentalists, is a positive and statistically significant predictor of identification with Share.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".