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Record W2968351148 · doi:10.1007/978-3-319-77440-4_12

Powers of Access: Impacts on Resource Users and Researchers in Myanmar’s Shan State

2019· book-chapter· en· W2968351148 on OpenAlexaff
Kirstine Roberts

Bibliographic record

Venue˜The œanthropocene: Politik - economics - society - science · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAsian Geopolitics and Ethnography
Canadian institutionsYork University
Fundersnot available
KeywordsLivelihoodNatural resourceState (computer science)Political scienceDisadvantageGeographyResource (disambiguation)Economic growthGovernment (linguistics)Environmental planningDevelopment economicsBusinessEconomicsAgriculture

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.811
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.019
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.074
GPT teacher head0.352
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2019
Admission routes1
Has abstractyes

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