Bibliographic record
Abstract
Abstract Along with a moment of peace in the middle of the 20th century came large changes in the world order; namely the rise of newly independent nations and the formation of supranational organisations. The Middle East was the first region to establish an intergovernmental security network after 1945 when the Arab League was created. While the institution has had several opportunities to prove itself capable of uniting and pacifying a region often described to be “without regionalism,” it has rather served as a tool in the toolbox of Arab nationalist leaders like Egypt’s Gamal Abdel Nasser to solidify their political legitimacy and maintain a strict policy of non-interference. The League’s failure to provide a place for mediation and resolution of regional conflicts further undermines its effectiveness. The Arab Spring that swept across the region beginning in 2009 brought optimistic projections for the League’s capacity to deal with the conflict, particularly following the League’s suspension of Syria following brutal repression of demonstrations in 2010. Is the failure of the League a product poor design at its offset or could it provide a hopeful forecast for increased regional cooperation and peacebuilding in the Middle East? Without bark and without bite, the latter will be difficult to achieve.
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.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".