MétaCan
Menu
Back to cohort
Record W1512431111

Assessing the Limitations of Laughter in Indra Sinha's Animal's People

2009· article· en· W1512431111 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenuePostcolonial text · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsLaughterReading (process)TRACE (psycholinguistics)Plot (graphics)Power (physics)SociologyAestheticsEpistemologyLinguisticsLiteraturePhilosophyArtMathematics
DOInot available

Abstract

fetched live from OpenAlex

This article assesses the limitations of laughter in Indra Sinha's Animal's People. I argue that the novel's cheeky first-person narrator draws on the languages of abjection and carnival to expose and thereby constrain the assumptions that both he and his implied readers may bring to intercultural reading encounters. I trace his explicit addresses to an imagined body of implied readers and the ways in which the uneven power relations that inform this relationship are reflected in the novel's plot. Drawing on the theories of Julia Kristeva and Mikhail Bakhtin, I analyze selected passages that show how the parameters defining what is laughable and what is not shift to make way for a potentially unsettling scene of reading both within the novel and in the larger text, which includes a website to which the reader is referred at the end of the Editor's Note. In conclusion, I argue that despite the novel's emphasis on the futility of genuine intercultural understanding, Animal's tactics produce new and possibly productive paradigms for reading what might be perceived as culturally different books.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score0.331

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 head0.061
GPT teacher head0.283
Teacher spread0.222 · 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