People-Centered Justice in International Assistance: Rule-of-Law Path Dependencies or New Paths to Justice for All?
Bibliographic record
Abstract
Abstract This paper reflects on the recent, rapid rise in the use of “people-centered justice” language in global policy and international cooperation contexts. People-centered justice has provided a valuable common language to achieve policy buy-in and structure discussions on achieving justice for all, and breakfree from path dependencies of earlier rule of law assistance, and donor support long dominated by top-down support to courts and formal institutions of the justice system. However, recent uses of people-centered justice—without additional clarity—gloss over crucial differences in how justice challenges are framed, which could risk undermining some of its initial progress, or repeating past challenges encountered with rule of law support. Experiences of the OECD, USAID and in the United Nations systems provide contrasting examples of charting new paths, or clinging to well-worn path dependencies. We conclude with several reflections to overcome concerns with current uses.
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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 | 0.040 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.089 |
| Scholarly communication | 0.027 | 0.030 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.008 | 0.020 |
| Insufficient payload (model declined to judge) | 0.011 | 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".