Bibliographic record
Abstract
Introduction Michel Foucault once told an interviewer that it was important to be humble in the face of apparent social irruptions. We should be properly alert, he said, to continuities of history and geography, and not constantly on the look out for markers of ‘the new’ or what today might be called ‘the post-’. This is surely good advice, and we need to bear it in mind when discussing issues like participation and good governance. The idea that states in the past have not been concerned with good government is clearly wrong. The emergence of biopolitics is one strong indicator of the responsibilities that governments are meant to have to their populations. Nevertheless, there is a strong perception in the development community that state failure and bad governance have become important issues since the 1970s, and this perception has been linked to a broader critique of rent-seeking behaviour, simple predation, and dirigiste development. In the next part of the chapter we review some of the debates that have attended the rise of the good governance agenda. We shall also follow Adrian Leftwich and Rob Jenkins in drawing attention to the ways in which the agendas of good governance can be said to depoliticize accounts of development and rule. They do so, not least, by refusing to pay close attention to questions of state capabilities, and the incapacity of some regimes to secure control over their territories.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 0.005 |
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".