Socialist-neoliberal Conservation: Hopeful Resilience within the Hoàng Liên National Park, Vietnam
Bibliographic record
Abstract
Abstract This article tackles some resilient discourses and strategies engaged by Hmong and Mien people living in Hoàng Liên National Park, a prominent conservation area of the northern Vietnamese highlands located in Sa Pa district, Lao Cai province, Vietnam. Facing the neoliberal transition of socialist institutions, economy, and ecology, communities living in and out of this mountain range must adopt enduring mindsets and demeanours to sustain their environmental imaginaries and ensure some future for their hard-earned livelihoods. Looking at this situation through everyday politics, we argue that resilience theory—when used duly—can help fill the gap between blatant opposition and straight acceptance and reveal the inconspicuous strategies of continuity and adaptations adopted by subordinated groups and individuals. Inside Hoàng Liên’s socialist-neoliberal conservation system, administrators apply principles of responsibilisation and co-management through private financing and development initiatives, and in the process, dumping much of the burden on highlanders’ shoulders. On the other hand, they hope to pursue their way of life, making the most of local opportunities. Such cohabitation causes undue pressures, which Mien and Hmong communities deal with by creatively engaging with, adjusting to, and evading the national park’s rationale while rangers keep a close eye.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".