Bibliographic record
Abstract
Teaching the topic of a country’s borders can be challenging. This is especially the case in Israel, where not all the state’s borders are agreed: there are internal disagreements between parties on the ground and external disagreements between parts of the international community and the State of Israel. A border, the very symbol of stability and consistency, contains mixed and contradictory aspects; the borders are not always well defined and, for many people, sensitive and contentious subjects. Therefore, teachers often avoid or feel uncomfortable teaching the topic, even though they know well its importance. This study examines existing curricula and textbooks used to teach the topic in Israeli high schools, and develops a picture of teachers’ perceptions of teaching the topic through qualitative research. On this basis, the paper proposes a training model that addresses both the social and emotional side of the subject and the historical and political knowledge required to teach it. The purpose of the model is to better equip and enrich teachers to take on the task while minimizing fear of encountering or provoking adverse reactions. The teacher’s role is to expose students to different perspectives and positions, so students can begin to assess the problematic and complex nature of the topic in general and Israel’s borders in particular.
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.034 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".