Immigrants in the Making: Media Analysis of South Asian Representation within Canadian Media
Bibliographic record
Abstract
This research aims to expand the area of South Asians within Canadian Media analysis. Currently there is little to no research in the area of South Asian representation in Canadian media in addition to this there is a need for research into Indian international students as they become more prevalent in Canadian News media as a result of a statement made by the Prime Minister Trudeau regarding Indias involvement in Hardeep Singh Nijjars death. It is important that during this time those of the South Asian community mainly Indian international students are not unjustly problematized within Canadian news media for immigrating to Canada during this time. This research utilizes a critical discourse analysis lens to analyze 144 Canadian news media articles from the Toronto Star, The Vancouver Sun, The Globe and Mail and CTV News over the span of one year to analyze how the discourse surrounding Indian international students has changed since the death of prominent figure Hardeep Singh Nijjar.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.017 | 0.006 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".