Bibliographic record
Abstract
Theoretically informed by the regulation school perspective and using a form of discourse analysis framed as an ideological critique, this thesis makes two general arguments. The first and most general is that the popularization of social capital theory is integral to the formulation of an emergently hegemonic discourse of communitarian liberalism that, I argue, is characteristic of a new mode of regulation. The second, and somewhat more specific, argument is that the adoption of social capital into the discourse of population health produces models of health disparities that run with the grain of communitarian liberalism. I argue that the political discourse of communitarian liberalism displaces a critical 'vertical' analysis of inequality as the outcome of dynamic relations of power and structurally determined differential access to resources. It offers instead, I suggest, a 'horizontal' analysis that posits inequality as static hierarchy and that focuses on behavioural aspects of 'exclusion': 'welfare dependency', the putative erosion of civic spirit, political disengagement, epidemic cynicism, and declining levels of trust and reciprocity, at the level of the individual. Social capital provides a timely idiom through which to articulate this horizontal problematic as a new politics of 'common-sense'. I argue that social capital theory in population health gestures toward a stance that invokes the category of the social as a means of enabling more sophisticated and putatively sociological forms of analysis and explanatory models (I call this the 'left wing effect'). The endeavour is ultimately characterized, I argue, by a failure to engage with the complex interrelated contingencies of social settings---a failure rooted in the reductive epistemological orientation (the 'abstract empiricism') of epidemiology and quantitative sociology---offering instead a handful of ahistorical and ostensibly universal proxies. Ultimately, I conclude, population health models deploying the concept of social capital tend to develop explanatory narratives that are congruent with communitarian liberal discourse and which foreground characterizations of the social determinants of health in terms of an individualized (psychosocial) problematic of exclusion (for which the antidote is a sort of moral reengagement in and through virtuous civil communities) rather than critical structural or systemic characterizations.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.069 | 0.016 |
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".