From Ananthi to Anna: Teacher Colonization of Student Names Among Tamil Canadians
Bibliographic record
Abstract
Teachers and classrooms in Ontario consistently communicate to Tamil students that their names are too long, too foreign, too difficult to pronounce, and a hassle for teachers to learn. Teachers colonize Tamil students’ names with the goal of making them as “white” and English as possible by systematically renaming, mispronouncing, and/or shortening Tamil names. I call this process the “colonization of names.” This paper explores the impact of the colonization of names amongst Tamil Canadians through critical race theory. I conducted six semi-structured interviews with Tamil Canadian adults who went to public school in southern Ontario and had childhood experiences with the colonization of their name. This study indicated that participants experienced grave consequences due to the colonization of their names, including anxiety and embarrassment, a lack of sense of belonging, a feeling of cultural displacement, and being forced to occupy dual identities by having two names (one used at school, and one used at home). Some participants maintained their colonized name, while others made efforts to reclaim their Tamil name. Regardless of how students choose to navigate this forced renaming, the Ontario education system, which is embedded in colonial and white supremacist structures, needs to be problematized and held accountable for the colonization of Tamil names, and for constructing the false narrative that non-English names need to be changed.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".