Bibliographic record
Abstract
Immigrant success stories found in English as a second language (ESL) textbooks used in government‐funded language instruction in Canada imagine Canada as a redeemer of immigrant newcomers. Through a critical discourse analysis of ESL textbooks used in Language Instruction for Newcomers to Canada classes in Ontario, I identify two primary strategies of legitimation: positive self‐representation/negative other‐representation (van Dijk, 2000) and the maintenance of a low orientation to difference (Fairclough, 2003), despite a feigning of dialogicality. The stories of these immigrant newcomers follow a very similar narrative pattern that legitimates periods of economic hardship, social exclusion, and personal struggle. However, they overwhelmingly represent hard‐working immigrant newcomers as successful and appreciative of the opportunities provided to them by Canada. I conclude by arguing that ESL teachers should recognize that the diverse experiences of newcomers may not align with these repetitive imaginings of Canada as a redeemer of immigrant others.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.018 | 0.013 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".