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Record W2233344886

Un/Authorized Exhibits: Elegiac Necropolitics in Renée Sarojini Saklikar’s children of air india

2015· article· en· W2233344886 on OpenAlexaffvenueabout
Tanis MacDonald

Bibliographic record

VenueStudies in Canadian Literature · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Cinema and Culture
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsPoliticsLawEconomic JusticeDutyElegiacSociologyHistoryMedia studiesPolitical scienceLiteratureArt
DOInot available

Abstract

fetched live from OpenAlex

Renee Sarojini Saklikar’s children of air india is a book which takes as its subtitle “un/authorized exhibits and interjections,” well aware of its position as public dirge, un/official archive of voices and names, and interruptive document to the official story of Air India Flight 182. Official accounts foreground the facts: there were 331 people -- including 280 Canadian citizens of South Asian heritage, 82 of whom were children under the age thirteen -- who died when a bomb exploded on that plane off the south-west coast of Ireland on June 23, 1985. The “un/authorized exhibits and interjections” of the text and its embedded grief politics are championed by an oppositional figure of a female mourner in public space as a critic of postmodernist “despairing rationalism,” much as philosopher Gillian Rose discusses in her elegantly-titled Mourning Becomes the Law (7). Rose asserts that the law, if it is still the law that serves the citizenry and not an ideology that serves itself, has no other ethical choice but to acknowledge this truth: female mourners, by insisting on mourning as an act of justice, “reinvent the political life of the community” (35). The literary and other artistic manifestations of such mourning duty, and the philosophical injunctions to challenge and trouble the law through persistent mourning, are central to the project that drives children of air india : to “write the names all the way through” (Saklikar 113).

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.029
GPT teacher head0.270
Teacher spread0.241 · 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.

Study designNot applicable
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
Published2015
Admission routes3
Has abstractyes

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