Children’s Rhetoric in an Era of (Im)Migration: Examining Critical Literacies Using a Cultural Rhetorics Orientation in the Elementary Classroom
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There is a particular urgency in this political moment to understand children’s experiences with current events. Drawing from data generated following the 2016 presidential election, this paper focuses on three racially and linguistically diverse children’s persuasive compositions. Within a critical literacies writing unit focused on (im)migrant experiences, children called on legislators to act on the Republican administration’s policies. Building on the understanding that all literacies are political and that teaching and learning are value-laden tasks, the author engaged a cultural rhetorics orientation—grounded in the understanding of texts, bodies, materials, and ideas as interconnected aspects of communication—for data generation and analysis. The findings highlight how children strategically employed rhetoric to persuade. They used logos, pathos, and ethos, as well as story, a central tool for meaning-making and building practices in the world. Ultimately, this study demonstrates how children, when properly supported, can agentively participate in critical literacies and act on real-world politics. Through the stories of young children, this study emphasizes what children have to tell adults and what a cultural rhetorics orientation, through its emphasis on story, enables literacies researchers and educators to understand about children’s composing.
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.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it