On language ideology and education policies: A conversation with Thomas Ricento
Bibliographic record
Abstract
Dr. Thomas K. Ricento is a professor emeritus of education at the Werklund School of Education at the University of Calgary in Canada. In 1987, he received his PhD degree in applied linguistics from the University of California, Los Angeles. Around his research interest in language policies in the context of minority languages in North America, he has conducted numerous international projects. He is the editor of the foundational reference work An introduction to language policy: Theory and method. Also, he is the author of the recent book Refugees in Canada: On the loss of social and cultural capital and has numerous books published in international venues. He has co-edited special issues in well-established journals such as TESOL Quarterly and Language Policy. Furthermore, his articles appeared in venues such as Journal of Sociolinguistics, Discourse & Society, and Journal of Language, Identity & Education. On 17 April 2023, Dr. Huseyin Uysal conducted this interview with Dr. Ricento virtually. Later, he transcribed the recorded audio and edited the text to maximize the readability.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.029 | 0.032 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.012 | 0.028 |
| 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".