Bibliographic record
Abstract
The sophistication of peace operations and complex humanitarian missions has increased in recent decades, resulting in increased international capacity to mitigate organized violence and provide relief to suffering populations. With respect to other indicators of success, however, international peace strategies still leave much to be desired. By their very nature, externally driven efforts tend to leave local actors feeling marginalized and disempowered, and unable to fulfill aspirations for cumulative and sustainable transformations in the quality of life. The peace that local populations genuinely hope for may fail to take root, and dynamics associated with interventionism may replace one set of problems with another. To address such problems within existing peace processes and to provide a framework for broader preventive action, this paper identifies “localizing peace” as a central challenge for twenty-first century peacebuilding efforts. International and cross-cultural cooperation remain vital for tackling border-spanning problems and structural inequalities, yet the advancement of global peace depends in no small part on the enhancement of local peace capacities. Ultimately, peace must be defined and constructed locally, and peacebuilding efforts become energetic and sustainable only to the extent that they tap local resources, empower local constituencies, and achieve legitimacy within particular cultural and religious contexts. By appreciating these realities, international actors can discover more effective means of partnering with local organizations and movements, while also deriving new insights into the unity and diversity of peacemaking.
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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 | 0.023 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.009 | 0.038 |
| Scholarly communication | 0.022 | 0.032 |
| Open science | 0.004 | 0.024 |
| Research integrity | 0.017 | 0.015 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".