Bibliographic record
Abstract
Sri Lankan Tamils are among the newest wave of immigrants in North American and European metropolises. Before the Sri Lankan ethnic conflict became militarized in 1983, Tamils left the island sporadically for educational purposes, and mostly to the colonial metropolis London. In the past 20 years, however, they have migrated in increasing numbers to many other locations in the West. I have been visiting three locations in particular – Toronto, London, and Lancaster (California) – since 1996 to understand the Tamil community’s orientation to English language (see Figure 3.1). Currently, according to the estimates of local Tamil community organizations, there are about 150,000 Tamils in Toronto (the largest community of Tamils in a single city outside Sri Lanka) and 50,000 in London.1 While they are scattered in the United States, Tamils form a cohesive community of about 35 families (120 people) in a small town populated by 121,000 people in Lancaster (approximately 60 miles north of Los Angeles). Though this is a smaller community (providing fewer subjects for research), I wanted to compare how a fairly close-knit immigrant community in a small town reflected the trends of scattered settlements in other urban locations.
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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 | 0.005 | 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 | 0.013 | 0.017 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".