White Citizenship: A Category of Identification and Route of US Immigrant Constitution
Bibliographic record
Abstract
The “desire to be white” observed amongst Filipino/Ilocano-Hawaiian immigrants is not a mere personal resolve nor a sole act of individual decision. It is an aspiration driven by the ideology of “white ideal,” the discourse of middle class success, and deepened/straited by the historical junctures such as the colonial and neocolonial relationships between the US and the Philippines, immigration policies, and the sugar plantation labor history in Hawaii. The control and discipline of Filipino/Ilocano-Hawaiian immigrants are installed through the iteration of normative rules involving identification categories of race, ethnicity, and class. The identification of white ideal however may get deflected in the crisscrossing and reception at the level of social praxis, as the attempt to embody a norm is never complete (Rottenberg). Such area of ambivalence may produce fissures that present critical space for the re-encodation of Ilocano-Hawaiian representation and agency. Of note is the seamless intrication between the history and the story, between texts and contexts, or conversely, between contexts and texts in selected GUMIL Hawaii short fiction. The play of “mirroring” of white ideals and the “disidentification” of the same is precisely recuperated in the study.
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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 | 0.011 | 0.013 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".