The Tiger (in)Flu(ence): Posthuman, Abject Bodies, ‘Speculated’ Femininities and Diasporic Subjectivities
Bibliographic record
Abstract
Written by Larissa Lai, a Chinese-Canadian writer who has always alchemized her production with Chinese mythology, The Tiger Flu (Vancouver: Arsenal Pulp Press, 2018) is a polyphonic novel because of the plurality of interpretative acts it evokes, and because of its interweaving of different literary frames and genres. In the first part of this essay, I analyse how Lai exploits this complex intertwining of genres to address a sense of diasporic belonging. In the second part, I explore how this approach leads to moving beyond normative and totalizing definitions. Lai sets up a multifaceted feminine space where issues about the rethinking of the category of woman, sisterhood and a broader conception of the community can be raised. I argue that Lai’s representation of non-normative female bodies becomes functional in revealing how abject bodies can challenge the hegemonic meaning of gender and identity. In a critical reading that cannot be divorced from a (trans-)Canadian context, I conclude by exploring how Lai guides her readers on an intimate journey across increasingly fluid borders and an unsolved (and unsolvable) vision of the future.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".