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Record W2266076237 · doi:10.7282/t39p30zg

Conditional futures

2011· article· en· W2266076237 on OpenAlexaboutno aff
Anantha Sudhakar

Bibliographic record

VenueRutgers University Community Repository (Rutgers University) · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFutures contractProduction (economics)HistoryGeographyEconomicsFinancial economics

Abstract

fetched live from OpenAlex

Conditional Futures: South Asian American Cultural Production and Community Formation, 1991-2001 traces the development of a politically engaged diasporic consciousness, expressed in contemporary South Asian American literature and other media during the period between the Persian Gulf War and 9/11. This diasporic consciousness sought to challenge the assimilationist, “model minority” selfrepresentation of a previous generation of South Asian American professionals. Responding instead to a set of transnational shifts that shaped the 1990s—including India’s economic liberalization in 1991 and the post-Cold War rise of U.S. military and commercial global dominance—contemporary South Asian American artists and cultural critics, such as Vivek Bald, Meena Alexander, Shani Mootoo, Amitava Kumar and Vijay Prashad, reframed diasporic community as cohering around shared politics, rather than shared origins. Drawing upon a grassroots archive of community organization newsletters, arts periodicals and personal interviews, my analysis reveals the multiple spatial scales of transnationalism that contextualize these artists’ and scholars’ projects: global changes in labor and migration as a result of economic liberalization, on one hand; and a hemispheric diasporic arts activism aligned with feminist, queer and antiracist organizing in New York City and Toronto, on the other. I locate aesthetic innovation as an important response to fiscal and social reforms during the premillennial decade, as it provided a creative plane through which artists imagined “conditional futures”—modes of collectivity that did not yet exist, but could possibly evolve.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.305
Threshold uncertainty score0.991

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0070.006
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.3050.063

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 head0.045
GPT teacher head0.211
Teacher spread0.167 · 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.

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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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