Bibliographic record
Abstract
Elementary social studies can and should be taught through an age-appropriate lens of complexity which includes multiple perspectives that students evaluate in order to form evidence-based claims. Social Studies textbooks have often been critiqued for oversimplifying historical events with sanitized versions of the past (Calderón, 2014; Ladson-Billings, 2003; Loewen, 2008; Peterson, 2008). The tendency in elementary social studies has been to smooth over conflict (Cowhey, 2006; Peterson, 2008). To help elementary teachers disrupt sanitized versions of social studies, I urge that we start trusting students to grapple with complex narratives. First, I demonstrate the prolific existence of sanitized stories in social studies textbooks. Next, a rationale for and descriptions of complex narratives are provided. Lastly, a ‘Complex Questioning Framework’ is presented to help educators identify sanitized social studies in order to add the necessary complexities.
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.
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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.032 |
| Scholarly communication | 0.018 | 0.027 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.007 | 0.015 |
| Insufficient payload (model declined to judge) | 0.018 | 0.008 |
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".