Strategic scarcity: The origins and impact of environmental conflict ideas.
Bibliographic record
Abstract
This thesis examines the origins and impact of environmental conflict ideas. It focuses on the work of Canadian political scientist Thomas Homer-Dixon, whose model of environmental conflict achieved considerable prominence in U.S. foreign policy circles in the 1990s. The thesis argues that this success was due in part to widely shared neo-Malthusian assumptions about the Third World, and to the support of private foundations and policymakers with a strategic interest in promoting these views. It analyzes how population control became an important feature of American foreign policy and environmentalism in the post-World War Two period. It then describes the role of the "degradation narrative" -- the belief that population pressures and poverty precipitate environmental degradation, migration, and violent conflict -- in the development of the environment and security field. Based on archival research and interviews with key policymakers, foundation officers, and scholars, the thesis identifies a process of "circumscribed heterodoxy" in which an illusion of openness to diverse views masks a politics of uniformity at both the project and policy level. It examines the intentional and unintentional effects of environmental conflict ideas on U.S. policy institutions, and considers the nature of the knowledge communities that formed around these ideas. In so doing, the thesis offers insights into the complex relationships between knowledge, power, and policy.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.032 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".