Reimaginando Norteamérica bajo el TLCAN: las redes teatrales de México y Quebec como caso de estudio
Bibliographic record
Abstract
What do cultural networks tell us about regional agendas? This document is part of a broader investigation into the productive networks of cultural exchange – specifically in the field of theater – between Mexico City and Quebec during the NAFTA/TLCAN/ALENA years (1994-2018). The paper explores the role that the work of imagining communities plays in regionalization processes, observing how this imaginative labor renders political agendas concrete, at the same time that it invisiblizes other forms of contact and cultural tensions within the region. The first section exposes the ambiguities and arbitrariness of geographic demarcations and of imaginative practices that transform space into a shared imagined place, be it city, nation or region. It presents a brief overview of the conceptual history of Latin America as necessary context in understanding the role that NAFTA played during the nineties in producing North America as an imagined region. The second section is a descriptive overview, without being exhaustive, of the primary networks of exchange between Mexico City and Quebec, specifically in the circulation of theater texts, artists, productions and translations generated during the twenty-five years of NAFTA. In the face of these maps of exchange, the paper asks: what does the relationship between idea and material infrastructure reveal about the role of cultural production in the political and economic inner-workings of a region? More specifically, what may be discerned from the analysis of Mexico and Quebec‟s theatre networks, of their political, economic and ideational intentions and strategies as regional actors?
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".