Market-Engaging Institutions: The Rule of Law, Resilience and Responsiveness in an Era of Institutional Flux
Bibliographic record
Abstract
Abstract This article analyses the institutional conditions required to support a strategic state in being responsive to the changing demands of a market-economy, whilst maintaining a credible commitment to long-term policy goals. This article identifies a key pillar of a market economy that we believe is crucial to promoting inclusive economic growth; we term these institutionsmarket-engaging institutions.We propose that market-engaging institutions may form a bridge between the flexibility required by a dynamic market economy and the stability demanded by the rule of law. We define market-engaging institutions as those institutions that facilitate greater political participation for marginalized groups, manage technological disruptions, and support human capital formation. Examples include social partnership agreements, collective bargaining coverage, trade union membership, education and training services, and research and development programmes. We suggest that mobilizing these institutions necessitates credible commitment. Further, we argue that through its commitment to the non-arbitrary administration of general rules the rule of law is an essential condition for signalling the state’s credible commitment. However, at times the requirement for the state to be flexible to the changing needs of market actors may conflict with the rule of law’s demand for constancy and stability. This article examines the delicate balancing act required to sustain a strategic, responsive, and credible state in an era of institutional flux.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.044 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".