Aligning Identity: Social Identity and Changing Context in Community-based Environmental Conflict.
Bibliographic record
Abstract
This research follows the “timber wars” in the Sierras of northern California from 1984 through 1996, including the formation of the controversial Quincy Library Group. Using a case study approach, the research explores the longstanding divisions between environmentalists, loggers, and the U.S. Forest Service and the role that social identity and social context play in perpetuating an intractable conflict and then helping to transform the local conflict as the social, economic, political and ecological context surrounding protagonists changed. Social identity theorists argue that individuals possess multiple social identities that become salient in different contexts or as context changes. Such identities exacerbate differences and can, when threatened, lead to intractable conflict and to common pool resource dilemmas characterized by “tragedy of the commons” situations. The research explores the use of identity and characterization frames by disputants in the context of the local timber and the way frames change, leading to the transformation of the conflict and the emergence of a new conflict at the regional and national level. Using a process theory framework, the research findings support the argument that external directional forces created conditions necessary for the recognition of a common fate, common identity, and positive interdependence between loggers and environmentalists, and for cooperation and collaboration to transcend hostility and conflict. Transformation of the longstanding conflict resulted from a probabilistic process between adopted leaders on both sides of the conflict in which a common identity and superordinate goal were framed by one side and, over time, accepted by the other. The research has relevancy for identity-based environmental and natural resource conflicts and public policy processes in which multiple users are competing for scarce resources or in which tragedy of the commons situations exist.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.016 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| 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".