The Relationship Between the West and the Middle East: Recipe for a Better Future
Bibliographic record
Abstract
It is claimed that the relationship between the Middle East and the West (the USA included) has been marked by intervention, stereotyping, and misunderstanding, and that it has been, unfortunately, changing for the worse because of the double standards employed by the West and the unconditional support for Israel. Despite this situation, a better relationship can exist if Westerners go beyond stereotypes, adopt a balanced policy in the Middle East, and treat Arabs and Muslims as peers. The discussion demonstrates that the West-Middle East relationship has been lacking balance, and, thus, it has been bringing about tension and violence, impeding understanding, furthering separation, fuelling mistrust, and thwarting any attempt at achieving rapport. It also shows that the way to ease tension is by Westerners' tolerating diversity, renouncing superiority, reconsidering their double standards, and recognizing Arabs and Muslims as central parts of the social fabric. It has been shown that the Western policy in the Middle East has been biased, and that Westerners' recognizing Middle Easterners as they are,adopting a balanced policy, and tolerating diversity constitute a recipe for a better future relationship.
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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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.023 |
| Scholarly communication | 0.012 | 0.025 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.010 | 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".