Reimagining Resources and Community Development
Bibliographic record
Abstract
This book analyzes the experiences of communities facing major challenges relating to resource dependency and community sustainability, drawing on specific examples from the Canadian province of Newfoundland and Labrador. It offers a methodology of self-analysis for communities facing similar challenges, inspired by the ups and downs, local strategies for self-analysis, and collaborative work toward new futures in this Canadian province. Life in hundreds of small coastal settlements revolved around the cod fishery, until the fishery was no more viable. Communities have had to rethink their strengths, reconsider their assets, and imagine potential futures in the wake of events such as colonization and the collapse of the fishing industry. Their experiences are relevant for other parts of the world where formerly central resources are depleted or lose their value, and communities face the need for transition. The capacity to imagine different futures is rooted in the ability to critically consider strengths and weaknesses alike. The authors skillfully dissect and illuminate the conditions that can enable the reconsideration of local assets and narratives, toward a more sustainable future. The variety of these conditions, ranging from social memory to public debate, policy tools and institutional capacity, decision arenas, paths for participation, and distributed strategic leadership, are laid out clearly and illustrated vividly through vignettes written by individuals who participated in the events described. This book culminates in a flexible yet clearly structured method of self-analysis, useful for communities interested in rethinking their strengths and working toward new futures. This book will appeal to students, scholars, and professionals interested in community development and redevelopment and offers a new understanding of the mechanics of local and regional resilience
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.068 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".