Cross‐border planning at the U.S.‐Mexico border: An institutional approach
Bibliographic record
Abstract
The general objective of this article is to contribute to the understanding of cross‐border issues from an urban planning perspective. Cross‐border planning in this article is approached as an institution‐building process whose primary emphasis is on the facilitation of collective action with regards to the shared natural, built, and human environments constrained by territorial politics and boundaries of nation‐states. It is argued throughout the paper that the existing institutional framework at the U.S.‐Mexico border has been the result of a “muddling through” process. The existing cross‐border planning institutions are the result of an adjustment process, to a great extent due to challenges to the status quo by border actors and organizations. The main conclusion of the article is that the environment and the uncertainty that this poses for the future is an issue that decision makers have been able to “muddle through” more successfully and should continue doing so by fine‐tuning and supporting existing institutions and continuing the incremental process of institution building.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".