Expanding Knowledge Gaps: The Function of Fictions in Teaching Materials after the 2011 Swedish High School Reform
Bibliographic record
Abstract
The aim in the study is to analyze how work with fiction is organized in six textbooks for senior high school in Sweden after the school reform 2011. Research into Swedish teaching materials has been neglected in recent years and there is a knowledge gap about how the work with fictions is affected by the reform in 2011. In the study quantitative and qualitative methods are used and Bernstein’s theories relating to horizontal and vertical discourse are applied to the empirical material. The analysis shows that work with fiction in textbooks is marginalized, particularly work with fictions created by women. The study also shows that students attending vocational programs have access to a different knowledge than students attending university preparatory programs. This is remarkable, since the learning objectives in Svenska 1, curriculum for vocational and university preparatory programs, are the same. This means that central values of equal education are eliminated after the reform, and the knowledge gap between different groups of students likely is to increase.
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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 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".