Bibliographic record
Abstract
Politics involves distinct social mechanisms, which cannot be adequately captured by the sociological notions of structure and culture, or by the economic concepts of rational choice and equilibrium. Some political actions are driven by social norms, and others by utilitarian calculations, but political life always contains an additional dimension: communication. Political scientists sometimes convey this distinction by speaking of a logic of arguing that exists alongside a sociological logic of appropriateness (norms) and an economic logic of consequentialism (utility). When they argue, social actors can challenge prevailing norms and the dominant rationality, and transform society as they communicate and deliberate. Economist Albert Hirschman once made a similar distinction by contrasting the market, where one exercised choice through “exit” – by not buying – and politics, where “voice” and protest were the prevailing modes of operation. Likewise, Jon Elster distinguished the market, where private preferences were expressed through purchases, and the forum, where an open and public conversation brought people to determine together the common good and the meaning of social justice. This deliberative dimension of politics is perfectly captured by the left–right opposition. Whereas the core concepts of economics translate into an instrumental rationality that tends to “close off debate,” the left–right division, understood as the core currency of political exchange, suggests instead that debates are unavoidable, inherent in political life, and foundational for democracy.
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.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.224 | 0.089 |
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".