Enacting subjectivities in educational history: methodological reflections on the use of qualitative interviews for history writing
Bibliographic record
Abstract
Two studies of the formation of pupils’ subjectivities within the Danish school and educational system in the period 1945–2005 create the framework for a methodological discussion of how subjectivities in educational history can be studied. Both studies use qualitative interviews as a way of studying subject formations in educational history. This methodological approach, however, exposes inherent methodological problems stemming from the use of sources produced in the present for studying the past. To address these problems the article will draw on poststructural ideas of subjectification and performativity developed by Judith Butler and suggest two analytical moves: A notion of time as temporality is put forward to rethink the problem of past/present in the work with memories as source material. Furthermore, the concepts of performativity and enactment are introduced to deal with the displacement of narrated subjectivities in the interviews. By this the interviewees are said to perform as memorising subjects while enacting different (memorised) subjectivities.
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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 | 0.161 | 0.097 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.020 | 0.071 |
| Scholarly communication | 0.021 | 0.018 |
| Open science | 0.005 | 0.019 |
| Research integrity | 0.005 | 0.007 |
| 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".