Innovation and public space: The developmental possibilities of regulation in the global south
Bibliographic record
Abstract
Abstract Important product and process innovations are often developed in “public spaces” that promote collaboration and provide shelter from market competition. Given that most collaborative spaces are costly to establish, the possible implications are bleak for economically strapped developing countries. This paper highlights a less conspicuous – if not unknown – source of collaborative space: the regulatory process. Regulators can induce innovation by promoting collaboration across organizational, sectoral, and disciplinary boundaries in the interest of regulatory compliance. This paper documents the innovative consequences of efforts to regulate the use of lead‐based glazes in the Mexican ceramics industry and reconsiders several recent studies of upgrading in other countries that appear to have been driven, at least in part, by the regulatory process. Drawing on these cases, this paper makes four primary points: (i) that innovation in regulatory spaces is more common than previously acknowledged and is producing meaningful improvements in product quality and working conditions in developing economies; (ii) that promoting innovation in these regulatory spaces is an important developmental tool for countries that are “regulation‐takers” and have many low‐tech sectors; (iii) that this dynamic extends current conceptions of regulatory discretion, as well as development literature on state‐society synergies; and (iv) that establishing collaborative public spaces as a common conceptual framework is a critical step toward understanding the consequences of social regulation on upgrading.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.033 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".