Writing Rights to Right Wrongs: A Critical Analysis of Young Children Composing Nationalist Narratives as Part of the Larger Body Politic
Bibliographic record
Abstract
Many researchers have considered recent and intergenerational immigrant children’s perspectives on immigration policies. Fewer have investigated nonimmigrant children’s views despite children’s sociopolitical identities forming long before they can vote. Drawing from data generated in spring 2017, the author illustrates how young children at an urban, midwestern school argued against the Republican administration’s (anti-)immigration policies. Framed as an ethnographic case study, the author focuses on how third graders enacted justice-oriented identities as they wrote to congressional representatives about contemporary immigration policies. By attuning to how children embedded multiple institutional and political contexts in their written rationale, the author explicates the tensions and possibilities for nonimmigrant children in writing policies and possibilities for tomorrow. Ultimately, the author argues adults must intentionally sustain children’s civic participation in ways beyond the niceties that plague early years classrooms.
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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 | 0.016 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.024 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".