Powers of Access: Impacts on Resource Users and Researchers in Myanmar’s Shan State
Bibliographic record
Abstract
Natural resources in the Shan State of Myanmar provide the base for livelihoods among rural populations, providing food, shelter, and medicine to regions where markets, clinics, and schools are scarce. Local wisdom talks about the three governments in the Shan State: The central Myanmar government, the Burmese military, and the local ethnic armed organizations (EAOs). These fragmented sovereignties directly impact not only local communities’ access to natural resources, but also the research methods used to understand this. Using two villages from along the Thanlwin River in the Shan State and the collaborative methods from this research project as case studies, this chapter unpacks rights-based, disciplinary and structural, and relational mechanisms of access to enforce control over natural resources; at times, to the advantage or disadvantage of local communities and the research process. By understanding the mechanisms of access behind fragmented sovereignties it becomes possible to better design research and to analyze the feasibility and impacts of policy implementations on the lives of local people.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".