Foucauldian Discourse Analysis: Moving Beyond a Social Constructionist Analytic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although social constructionism (SC) and Foucauldian discourse analysis (FDA) are well established constructionist analytical methods, this article propose that Foucauldian discourse analysis is more useful for qualitative data analysis as it examines social legitimacy. While the SC is able to illuminate how the “meaning” of our social action is constructed through our everyday interaction in socio-cultural and political contexts, questions emerge that are beyond the scope of the SC. These questions are concerned with understanding how the construction of “meaning” is connected to the power imbalance in our society, as well as how a particular version of reality comes to us as truth, having excluded other versions. Moreover, SC does not distinguish between successful and unsuccessful/marginalized claims. This article reflects on how using FDA addresses weaknesses in SC when used in qualitative data analysis, using specific examples from different literature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it