Who benefits from state investment? Interrogating distribution under (urban) state venturism
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
This commentary traces the longer history of what Su and Lim refer to as urban state venturism as a means of posing questions about the distribution of benefits and risks which result from this model of state investment. Drawing upon the history of the Hudson Bay Company's role in both securing profits and building the British settler colonial empire, we ask how these state projects shape political economic processes beyond regional economic competitiveness. Specifically, we focus on how political projects of stigmatization and marginalization may interact with the geographies unleashed by urban state venturism and how they articulate with other priorities of the state. Through this generative critique we hope to build upon the potential of Su and Lim's work to contribute to debates in economic geography over state capitalism, the blurred lines between public/private finance, and questions of who benefits from these arrangements.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it