Funny Boy and the Pleasure of Breaking Rules: Bending Genre and Gender in "The Best School of All"
Bibliographic record
Abstract
This paper focusing on the fifth of the six stories, “The Best School of All,” that constitute Funny Boy , explores sexual identity politics on the school campus, by analysing how Selvadurai’s appropriation of the generic English school story, invests the popular genre with a disruptive potential, unknown to its original form, thereby generating immense pleasure in the reader. The paper argues that the pleasure in reading “The Best School” independent of the novel is to discover in it the familiarity of the school story, and also how it is constantly de-familiarised. By relating theories of genre, gender, nation and the diaspora, the paper attempts to show that “The Best School,” not only subverts generic rules by transfiguring an overtly masculinist genre to accommodate queer desires; it also opens up a dialogic space by confronting authoritative discourses on the colonial system of values perpetuated through the educational institutions, compulsory heterosexuality and ethno-centric nationalism of the postcolonial nation-state. In effect, “The Best School” becomes an important node in the dialogic network of queer narratives produced across the globe, qualifying as a “cause” novel: it advocates recognition of non-heteronormative identities and desires in a postcolonial nation, which is politically and morally opposed to legalising homosexuality, still criminalised under a Draconian colonial law.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.032 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".