Un/productive Raciality and Transnational Affiliations in Lydia Kwa’s<i> Pulse<i/>
Bibliographic record
Abstract
This paper explores the intersections that develop as Canada and Singapore redefine the terms of their productive raciality through their respective multicultural/multiracial forms in order to remain globally competitive. It draws out these intersections as they appear in Lydia Kwa’s Pulse (2010) through its engagement with the limits of “productive” raciality and the desires of the sexual racial body. Set both in Singapore and Canada, Pulse explores the everyday experiences of the particular figurations that are bracketed out through the rhetoric of productive raciality in both nations – including the Asianfication of Canada’s identity and Singapore’s use of “Asianism” as part of their global multicultural identities. As Pulse considers the effects of these states’ failure to facilitate frameworks that would make ostensibly “unproductive” transnational figurations legible to others, it also draws out new affiliations between these bodies subjected to these effects across these distinct contexts.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.017 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".