Environmental Conflicts, Migration and Governance
Bibliographic record
Abstract
The current era of globalization is characterized by a high degree of interconnectedness across borders and continents. This not only goes hand in hand with significant levels of international trade and foreign direct investments but also with migration, which is all too often driven by conflicts of various kinds. While various interdependencies between conflict and migration have been explored in the literature, a link that is not yet sufficiently understood relates to the interdependencies between environmental or resource-related conflicts and migration as well as the role of governance in this respect. This book strives to overcome some of these shortages in providing an interdisciplinary analysis of the interconnectedness between environmental and resource conflicts and migration. To this end, the contributions of this book address four core questions: (i) When do environmental and resource-related problems lead to conflicts and how does this create incentives for migration? How does the governance of natural resources either reduce or enhance the chances of conflicts and migration to emerge? (ii) Who leaves a country and where do migrants go? Which migration governance arrangements are at play in mediating conflicts and in directing migration flows? (iii) How do the trajectories of national, regional and international migration governance regimes look like? How effectively do they regulate environmental or resource-related migration? (iv) Which effects does migration have on possible conflict dynamics in destination countries and what is the role of governance arrangements in this respect? How do host countries participate in governance for the prevention of environmental or resource-related conflicts in countries of origin in order to reduce or prevent migration?
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".