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Record W4323648177 · doi:10.4000/ebhr.944

Swargajyoti Gohain, Imagined Geographies in the Indo-Tibetan Borderlands: Culture, politics, place

2022· article· en· W4323648177 on OpenAlexaff
Mark Turin

Bibliographic record

VenueEuropean Bulletin of Himalayan Research · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsLearning Partnership
Fundersnot available
KeywordsPoliticsIndo-PacificAnthropologyGender studiesGeographyHistorySociologyPolitical science

Abstract

fetched live from OpenAlex

The people of Monyul, a Tibetan Buddhist cultural region in west Arunachal Pradesh, Northeast India, hold aspirations for local autonomy.In this sophisticated monograph, anthropologist Swargajyoti Gohain explores the many textures of Monpa ambitions as these are 'overlaid by transregional imaginations that are pan-Himalayan in nature' (p14).2 Rooted in long-term fieldwork in Tawang and West Kameng districts, Gohain's text is one of continued intellectual refinement, exploring the complex cultural identities (language, place names, oral traditions) and transregional networks of connection that shape contemporary politics in Monyul.Gohain's analysis is set against the indelible backdrop of the unresolved border dispute festering between India and China.Imagined Geographies takes on a great deal and Gohain has high expectations of what she can convey in her text as well as what her reader can digest.At no point in this engaging and textured monograph are we at all disappointed.Imagined Geographies is contemporary anthropology at its very best: ethnographically rich, analytically rigorous and theoretically omnivorous.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.004
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.344
Teacher spread0.296 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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