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Record W4385582650 · doi:10.1111/sena.12391

Tibet’s response to state nationalism: Utilising China’s fear of secession

2023· article· en· W4385582650 on OpenAlexaff
Hari Har Jnawali

Bibliographic record

VenueStudies in Ethnicity and Nationalism · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Ethnic Minorities and Relations
Canadian institutionsBalsillie School of International AffairsUniversity of Waterloo
Fundersnot available
KeywordsNationalismSecessionChinaAutonomyPoliticsState (computer science)Political sciencePolitical economyTerritorial integrityIndependence (probability theory)Government (linguistics)Centralized governmentGender studiesSociologyLawSovereignty

Abstract

fetched live from OpenAlex

Abstract Taking document analysis as its method, this paper examines the Tibetans’ response to the Chinese state nationalism. Due to the fear of political secession, the Chinese government has stayed silent about the Tibetans’ right to self‐determination and subjected regional ethnic autonomy to the centralised political system. The Chinese authorities continue to dismiss the Tibetans’ nationalist struggles as an imported foreign design and warn the international community not to sympathise with the Dalai Lama and his supporters. Amidst an adverse national and international political environment, the Tibetans have managed to sustain their nationalist wishes and obtain substantive international attention. Taking this background into account, this paper explores how the Tibetans have succeeded to resist China's state nationalism and position themselves as a champion of inclusion, justice, and minority rights. It argues that the Tibetans recognise the Chinese government’s fear of secession and utilise that fear to forward their nationalist aspirations. The Tibetans shift their demand from independence to autonomy and highlight their own desire for recognition as a distinct community within the Chinese state. This strategy has helped them to claim that they are against the violations of autonomy but not against the Chinese state’s territorial norms.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.100
GPT teacher head0.442
Teacher spread0.341 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2023
Admission routes1
Has abstractyes

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