Governing Infrastructure in the Age of the “Art of the Deal”: Logics of Governance and Scales of Visibility
Bibliographic record
Abstract
Abstract Many different types of organization provide public services or goods and build public works without being, strictly speaking, part of government. Such entities tend to be seen as more innovative than government proper, both because of their organizational autonomy and because they primarily use private‐law techniques (contracts, mainly) and lay claim to private sector credentials. This article examines the presumed correlation between moves towards greater public‐private hybridity in government and public sector innovation, using illustrative examples from Ontario and British Columbia, Canada. Combining interviews with professional infrastructure deal‐makers, direct observation of public infrastructure workshops, and analyses of the documents that constitute infrastructure deals, we show that the quest to bring virtues and techniques associated with private enterprise to the delivery and governance of public goods and services often leads to a dialectical reversal. At first, bureaucratic rules do give way to the pursuit of more or less sui generis deals. But the entities that initiate deals and partnerships soon come to feel the need to standardize the process, which then leads to the return of standard templates and surprisingly rigid rules.
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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.082 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".