Reading and Oral Literacy in Disadvantaged Communities: Quebec Preschool and Primary Teachers' Perceptions and Practices
Bibliographic record
Abstract
Children who have difficulty learning to read are most common in disadvantaged communities (Brodeur et al, 2010). Several studies have shown that oral skills are rarely taught in class (DolzS LafontaineM LafontaineD Maltais, 2007; Terwagne, 2006; Senechal, 2006). The primary objective of the current research-training project (2010-2012), funded by a provincial program requiring a university-community partnership whose aim is the high-level professional development of educational practitioners, is to offer training and research seminars in reading and oral literacy to preschool and primary teachers in three schools in disadvantaged communities in Quebec who work with regular students as well as those with language challenges. The project's specific objectives are to guide teachers in the development and experimentation of situations involving literacy learning and evaluation, and to study the impact of the seminar on the integration of the concept of literacy and the renewal of practices. The proposed communication will examine the evolution of teachers' perceptions of reading and oral literacy based on the analysis of four questionnaires, four focus groups, and two semi-directed interviews conducted between September 2010 and April 2012. The ways in which the concept of literacy was integrated into daily practice as well as how the training the teachers received positively affected their practice for the better of their students will be presented.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".