Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Security sector reform (SSR) and small arms and lights weapons (SALW) reduction and control programmes have become staples of peacebuilding policy and practice in fragile, failed and conflict-affected states (FFCAS). There is wide agreement in the peacebuilding field that the two areas are intricately interconnected and mutually reinforcing. However, this consensus has rarely translated into integrated programming on the ground. Drawing on a diverse set of case studies, this paper presents a renewed argument for robust integration of SSR and SALW programming. The failure to exploit innate synergies between the two areas in the field has not merely resulted in missed opportunities to leverage scarce resources and capacity, but has caused significant programmatic setbacks that have harmed wider prospects for peace and stability. With the SSR model itself in a period of conceptual transition, the time is ripe for innovation. A renewed emphasis on integrating SSR and SALW programming in FFCAS, while not a wholly new idea, represents a potential avenue for change that could deliver significant dividends in the field. The paper offers some preliminary ideas on how to achieve this renewed integration in practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it