Enduring Effects: Name Mispronunciation and/or Change in Early School Experiences
Bibliographic record
Abstract
A person’s name(s) is typically tied to their family, culture, and sense of identity. Consequently, when a child’s name is inaccurately pronounced, altered, or avoided, a host of adverse consequences may transpire. Although seemingly innocuous, this necessitates attention, as name mispronunciation and change perpetuate microaggressions ubiquitous for marginalized populations, often in school contexts. In reflection of this, an Intrinsic Case Study, underpinned by a Social Constructivist Philosophical paradigm, was conducted to assemble the experiences of three adults in Ontario, Canada, who had their names mispronounced or changed in early educational experiences. The findings of this research signify that name mispronunciation and modification are pervasive and that teachers are often central contributors to this phenomenon. Moreover, findings denote that discord between one’s identity and cultural self is affiliated with name-orientated microaggressions. Participants of this study beseech teachers to denounce insensitive practices by pledging to accurately pronounce and honour each child’s name and in so doing engender more favourable longitudinal outcomes.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".