THE VIABILITY OF ISSUE RECONCEPTUALIZATION IN THE ARAB-ISRAELI CONFLICT
Bibliographic record
Abstract
The Israeli-Palestinian conflict is one of the most notorious intractable conflicts of the century. Historically, two streams of thought have dominated the academic realm of conflict resolution and reconciliation efforts: those which focus on reconciling final status issues, and those which focus on reconceptualizing identity. However, what has been neglected is the relationship between the two, or how identity affects individual’s perspectives on final status issues. As such, I propose that through re-conceptualization of issues, perspectives can be altered in such a way so that final status issues are no longer viewed as zero-sum. Such a re-conceptualization subsequently lays the foundations for more effective reconciliation and resolution efforts as both sides can envision potential gains. While this in itself is not an all-encompassing solution due to the dynamism of the conflict, when used in conjunction with other methods it provides yet another opportunity for open discussion and debate concerning resolution and reconciliation.
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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 | 0.068 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.015 | 0.037 |
| Scholarly communication | 0.023 | 0.023 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".