Bibliographic record
Abstract
Minhas incursões pelo vasto campo dos estudos de sociologia do direito não passaram pela sub-área de “direito e desenvolvimento” e, portanto, meus comentários aqui não tratarão da contribuição do livro Institutional Bypasses, de Mariana Prado e Michael Trebilcock, para essa literatura. Em vez disso, falarei da perspectiva da pesquisa em sociologia do direito sobre governança. Meu trabalho sobre governança — principalmente governança urbana (Valverde 2012) e, recentemente, a governança de parcerias público-privadas (Valverde e Moore 2019) — baseia-se, de maneira eclética, em diversas fontes. Substancialmente, li trabalhos de estudos urbanos e geografia jurídica (e mais recentemente um pouco sobre o financiamento de infraestruturas) (Blomley e Bakan 1992; Cooper 1998). Metodologicamente, utilizo Foucault (2007; 2010; 2003) e estudos sobre governamentalidade (Burchell, Gordon e Miller 1991), teoria do ator-rede e trabalhos a ela relacionados (Latour 2007; Callon e Latour 1981; Lei 1986), principalmente por antropólogos, sobre a materialidade do direito e também estudos pós-coloniais (Spivak 2013; Mawani 2010).
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 | 0.019 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".