Bibliographic record
Abstract
This dissertation is centered around questions concerning the social (social ontology) and its relationship to social research. One of its major reference points is the philosophical system (characterized as emergentist systemism in this dissertation) developed by the accomplished Argentinian-Canadian physicist and philosopher Mario Bunge. This dissertation draws extensively on the research findings of natural and social sciences, both in America and Europe, to argue for a systemist (i.e. transcending both macro- and micro-reductionism), realist, and critical approach to social ontology. In particular, Luhmann’s, Bunge’s, and critical social systems theorists’ formulations of social ontology, as well as Luhmann’s premature shift of focus from ontology to epistemology, are discussed and evaluated in depth. The approach developed in this dissertation is also extended to contribute to the wider debates within sociological theory and analysis, including the project of analytical sociology (as advanced by, among others, Peter Hedstrom and Jon Elster), critical realism, reductionism, emergence, micro-macro link, social structure and human agency, dialectics of nature, and causality and mechanism-based (microfoundational) explanations in social science.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".