Building Bridges Instead of Walls: Engaging Young Children in Critical Literacy Read Alouds
Bibliographic record
Abstract
Situated in the months after the 2016 United States presidential election, this qualitative case study illuminates third-grade children’s sense-making about the GOP Administration’s proposed border wall with Mexico. In light of these present-day politics, close analysis of how young children discuss social issues remains critical, particularly for social studies educators. Looking across fifteen book discussions, we zero in on three whole-class conversations about (im)migration beginning with initial read alouds through the final debrief wherein children conversed with a local university anthropologist about the clandestine migration of individuals across the U.S.’s southern border. During initial discussions, children in the Midwestern school demonstrated their frustration towards racist laws of the mid-1900s. Others responded with empathy or made personal connections to their own family heritage. In the findings, we note a clear progression in how children understood (im)migration issues as evidenced by how their questions and curiosities shifted in later lessons. We highlight how, when children are encouraged to engage with social topics, they can act as critical consumers and position themselves as politically active and engaged citizens.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".