Piecing it together, studying public–private partnerships
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Access to Information and Freedom of Information (FOI) mechanisms are increasingly used to gather data about state surveillance, security and intelligence. However, the rise of new public management and entailed chains of custody and control challenge the utility of these mechanisms for gathering information. While not suggesting a repositivising of social science research, I contend these oligoptic mechanisms – when pieced together with document analysis, interviews and participant observation – are a valuable means of gathering insights into the creation and nature of public–private partnerships, and interoperability of para-governmental agencies more broadly. This chapter traces one such public–private partnership – the creation of a business improvement area security information sharing network. Established in the aftermath of the Stanley Cup Riot and Occupy Vancouver, I highlight various vantage points into studying this policing network. These additive and cascading methods, when overlaid, help make sense of the mess, multiplicity and constitutive influence of FOI data production.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 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 it