Securing cross-border collaboration: transgovernmental enforcement networks, organized crime and illicit international political economy
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
ABSTRACT In a globalizing world, cross-border enforcement networks are rapidly emerging as important mechanisms to tackle illicit transnational markets. As a relatively recent mode of cross-border governance, both the IPE and public policy literatures have only just begun to explore the dynamics and implications of cross-border policy networks in general and security networks in particular. Cross-border enforcement networks are similar to current IPE conceptions of transgovernmental networks, yet the comparative analysis of such networks in this article shows that they extend, and differ, from transgovernmental networks. Instead, transgovernmental enforcement networks are emerging as a comparable but distinct transnational model and thus warrant emancipation as an object of study in their own right. By exploring two network cases concerned with US-Canada cross-border tobacco smuggling, the article discerns and describes factors and conditions that account for different outcomes among select U.S-Canada cross-border security networks: IBET/Shiprider and MYGALE. Data was collected by analyzing open primary sources and conducting interviews with subject participants in these policy networks. Based on these observations, the article generates insights that can subsequently be scrutinized using other cross-border policy case studies.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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