Bibliographic record
Abstract
The 6th book of the International Review of History Education Series, Contemporary public debates over history education, presents public debates on history education as they appear in 14 different areas of the world, in Asia, Europe, North and South America. In alphabetical order: in Brazil, by Maria Auxiliadora Schmidt and Tânia Braga Garcia, in Canada, by Peter Seixas, in England, by Rosalyn Ashby and Christopher Edwards, in Greece, by Irene Nakou and Eleni Apostolidou, in Israel, by Eyal Naveh, in Japan and South Korea, by Yonghee Suh and Makito Yurita, in Northern Ireland, by Alan McCully, in Portugal, by Isabel Barca, in Quebec (Canada), by Jean-Francois Cardin, in Singapore, by Suhaimi Afandi and Mark Baildon, in Spain, by Lis Cercadillo, in Turkey, by Dursun Dilek and Gülcin (Yapici) Dilek, and in the United States, by Peter Stearns.By illuminating common trends, national peculiarities and differences, this collective book further enriches our knowledge about crucial issues concerning public perspectives over history education in diverse parts of the world. It opens new questions and issues to be further investigated by all who are interested in this field, in terms of its historical, educational, global, national, ethnic, cultural, social and political dimensions in the current transitional and multicultural environment. This international dialogue therefore addresses historians, history education researchers, university professors, school teachers, policy makers, publishers, parents and all those who insist that history education is very important, especially if it enables young people to orientate in the present and the future in historical terms
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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 | 0.014 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.019 | 0.016 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".