An Integrated Model of Legal Transplantation: The Diffusion of Intellectual Property Law in Developing Countries
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
Why do some countries adopt exogenous rules into their domestic law when those rules contravene their specific interests? We draw on the policy-diffusion literature to identify four causal mechanisms that we hypothesize explain the adoption of such rules. While existing literature treats these mechanisms as independent, we argue that each works in combination with the others to facilitate legal transplantation. While one mechanism—coercion—tends to initiate the transplantation process, it fades over time and three others largely supplant it: contractualization, socialization, and regulatory competition. These mechanisms act in a mutually supportive manner. We test our claims via a quantitative analysis of legal transplants in the field of intellectual property (IP) that incorporates an original index of IP protection in 121 developing countries over more than 14 years. This article concludes with a plea for theoretical eclecticism, acknowledging multicausality and context-conditionality. Any comprehensive explanation of legal transplantation must include the identification of mutual reinforcement between causal mechanisms, rather than simply rank their relative contributions.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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