Reframing Identity Politics 1.0 to 2.0: A Postpositivist Response to 21st Century Sinophobia
Bibliographic record
Abstract
Decried by both sides of the political spectrum, identity politics continues to be the source of tension across the world. To address the problem, this article looks into the impact of Sinophobia on diasporic Chinese-identified individuals in Vancouver and Sydney under the rise of China in the 21st century today. This article argues how its common mode of practice (Identity Politics 1.0) is grounded on a positivist notion of identity politics that fosters divisiveness and hostility. Drawing on Stuart Hall’s work on diasporic identity, it analyzes how the politics of identity can be reconfigured to remain a tool for social justice as it was originally proposed in the Combahee River Collective Statement in 1977. In this multi-sited inquiry, data was collected through a combined method of interviews and ethnographic fieldwork, as well as sourcing data through various forms of digital archives. The purpose is to explore the identity formation process of individuals to examine how they negotiate their Chineseness within three levels of societal relations : interpersonal, municipal, and national. The findings unpack a postpositivist framework called Identity Politics 2.0 that re-conceptualizes identity where, as Tony Bennett suggests, its process can disrupt hegemonic formations so that new meanings of identity are generated to affirm one’s humanity and new political directions can emerge to support social justice and foster coalition across differences particularly under shared problems of an interconnected world.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.050 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".