Multiple Schools, Languages, Experiences and Affiliations: Ideological Becomings and Positionings
Bibliographic record
Abstract
This article focuses on the identity accounts of a group of Chinese children who attend a heritage language school. Bakhtin’s concepts of ideological becoming, and authoritative and internally persuasive discourse, frame our exploration. Taking a dialogic view of language and learning raises questions about schools as socializing spaces and ideological environments. The children in this inquiry articulate their own ideological patterns of alignment. Those patterns, and the children's code switching, seem mostly determined by their socialization, language affiliations, friendship patterns, family situations, and legal access to particular schools. Five patterns of ideological becoming are presented. The children’s articulated preferences indicate that they assert their own ideological stances towards prevailing authoritative discourses, give voice to their own sense of agency and internally persuasive discourses, and respond to the ideological resources that mediate their linguistic repertoires.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.012 | 0.019 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".