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Contagion and its Guises: Inequalities and Disease among Tibetan Exiles in India

2008· article· en· W2171317517 on OpenAlexaboutno aff
Audrey Prost

Bibliographic record

VenueInternational Migration · 2008
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsStigma (botany)RefugeeDiseasePremisePoliticsInequalityTuberculosisGender studiesSociologyEthnologyPolitical scienceGeographyMedicinePsychiatryLawPathologyEpistemology

Abstract

fetched live from OpenAlex

Abstract The paper outlines the trajectories of Tibetan refugees afflicted by tuberculosis (TB) within the exile community of Dharamsala (H‐P). These stories reveal the political nature of TB status disclosure, highlighting the often conflicting ways in which the disease is perceived among different Tibetan exile regional and generational groups. On the basis of these case studies, I aim to show that differentiated experiences of treatment and stigma within “intermediary” host communities such as Dharamsala partially determine the ways in which Tibetans deal with the risk of TB in their “onward” journeys further afield, in Europe, Canada and the United States. With the now well‐established connection between migration‐related stresses and the onset or reappearance of TB symptoms, we may need to consider that, in some cases, it is the compounding of attitudes to disease in “intermediary” diasporic communities with the stigmatising label of “migrant menace” in the second stages of migration that impedes the care of migrants and even precipitates illness. With this premise the paper proposes that investigations of disease in diasporic communities should explore the totality of migration “stages” and their impact on health.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.034
GPT teacher head0.325
Teacher spread0.292 · 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 designObservational
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

Citations7
Published2008
Admission routes1
Has abstractyes

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