But what do You mean? A multiple case study of semiotic demands and supports in elementary classroom curricula
Bibliographic record
Abstract
Evidence to support multimodal pedagogy that considers how modes vary across disciplines, as constructed by the teacher and the student, is limited. This is potentially problematic when considering the type of connection that could arise between facilitation of modes by the educator to the semiotic demands (expressive and receptive meaning making expectations) placed on students through the various modes that they use or expect students to use. As such, how these resources are employed across disciplines, and in what combinations are necessary to study further to expand communication options. This doctoral thesis study investigates multiple cases of the semiotic demands placed on elementary students across the disciplines of Language Arts, Mathematics, and Social Sciences. Using data collected from three elementary teacher participants via interviews, assessment examples, ethnographic methods, and audio recordings which are analysed using multimodal analysis (Jewitt, 2009), the study will work to create new knowledge about how teachers can foster inclusive classrooms where all students are supported to make meaning across the curriculum. The results of this study may be used to support educators to recognize the semiotic demands they and the classroom curriculum
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.012 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".