History Wars in Sweden? : A syllabus debate about nation, history, and identity
Bibliographic record
Abstract
History teaching and learning in schools has been the subject of history culture wars in countries such as Sweden, Australia, the US, and Canada. In a Swedish-specific context, this and similar debates should be viewed in relation to the fact that throughout the twentieth century, governments in Sweden, as well as other countries, have regarded history teaching in schools as an important builder of national consciousness. At the same time, Sweden has undergone substantial demographic changes in recent decades. This article analyzes the different perspectives put forward in a debate on the school subject of history in Swedish education as a new syllabus was being introduced. Seixas' approaches to history are used in the analysis. The debate was initiated by historians who criticized the syllabus for the absence of the period of Antiquity. Leading politicians also participated. The collective memory approach was a central perspective on history in schools in the debate.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.022 |
| Scholarly communication | 0.020 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".