Discourse / Discours - Rethinking Case Study Methodology in Poststructural Research
Bibliographic record
Abstract
Little consideration has been given to how case study might be used in poststructural research to explore power relations that constitute a phenomenon. Many case study scholars, most notably Robert Yin, adopt a postpositivist perspective that assumes the truth can be accessed through applying prescriptive and rigid research techniques. Using a discussion of Michel Foucault's key theoretical ideas and the insights gained through a Foucauldian case study of people with advanced cancer who continue to receive curative treatment, the authors argue for the expansion of case study in poststructural inquiry. They propose that the use of poststructuralist case study is valuable because of the flexibility and comprehensiveness of the methodology, which allows for the exploration of a deeper understanding of the broader discourses that shape a phenomenon, as well as how power/knowledge relations shape the behaviours and perceptions of people. They also introduce the reflexive implications of poststructural case study research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.066 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".