Structural or dialectical hermeneutics? Further epistemological, theoretical and methodological questions in Jeffrey C. Alexander's cultural sociology
Bibliographic record
Abstract
Jeffrey C. Alexander's strong program in cultural sociology relies on what he calls a structural hermeneutics for interpreting social life. This approach is based on the binary oppositions that organize and codify the underlying references of social discourses and performances in the civil sphere. Yet the relations at stake between these social discourses and performances and their underlying references are considered, through structural hermeneutics, in their static state, contradicting the dynamics of formation and transformation of the civil sphere to which they refer. This article proposes to go back to the epistemological debates that fueled the introduction of hermeneutics in Dilthey's Geisteswissenschaften program, in order to show that what is truly at stake in interpretation is the dialectical, and not only structural, relations constitutive of the civil sphere. Once this is done, the strong program of cultural sociology can be revised to take into account the dialectical hermeneutics according to which the codification and organization of social discourses and performances are produced. Subsequent to this theoretical orientation, examples are introduced on the methodological level, drawing on George Herbert Mead's conceptualization of self and society, highlighting in a different manner the analysis of the civil sphere presented by Alexander.
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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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.072 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 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".