Constructions of gender in preschool, preschoolclass and primary school.
Bibliographic record
Abstract
The paper is based on work conducted in my dissertation that aims to explore gender constructions in preschool, preschool class and the first grade. In the analysis, gender constructions as they appear in children’s interactions and between children and adults are explored. Barrie Throne’s (1993) concepts borderwork and crossing are of theoretical importance in the study. The dissertation consists of two studies based on different sorts of empirical data. In the first study, video recordings from the FISK project [The Preschool and School in Collaboration Project] are re-analysed. The analysis takes its starting point from conversation analysis (CA). The second study consists of data collected from a separate fieldwork carried out in a preschool class, for which I have been personally responsible. On the whole, the analysis shows that borderwork situations are more frequent than border crossing. Gender boundaries were strengthened by the way the teachers interacted with the children. Also the children were part in this as for how they reacted to behaviour that was considered inappropriate. Especially boys experienced this, but what differs from previous research is that boys more frequently challenged gender boundaries. The recurring borderwork situations raise questions about equality in preschool, preschool class and school.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".