Contributions of Reading Support from Teachers, Parents, and Friends to Reading Related Variables in Academic and Recreational Contexts
Bibliographic record
Abstract
Abstract Reading skills are considered an important lever for success in school and active participation in society. They are positively associated with reading motivation, reading self‐concept, reading frequency, and behavioral engagement in reading (e.g., time, effort), variables that tend to decline as students move from elementary to secondary school. Few studies have yet compared the contributions of reading support from teachers, parents, and friends to each of these variables among students of different age groups. In this multicohort correlational study, students ( n = 1246) in grades 4, 6, 8, and 10 completed a questionnaire measuring the reading support they perceived receiving from three social agents (teacher, parents, and friends) as well as variables related to reading in academic and recreational contexts. The data collected were used to evaluate the construct relevance and predictive validity of the questionnaire. The results suggest that: (1) Reading support can be conceptualized in nine dimensions defined according to the source that provides it (e.g., teachers) and the type to which it corresponds (e.g., relatedness support); (2) secondary school students overall consider that they receive less reading support than do elementary school students; (3) reading support from teacher has unique contributions to certain variables measured in the academic context without, however, having as many positive contributions as parents in this context; (4) reading support provided by parents and friends is important in both reading contexts, particularly in the recreational context. Methodological, theoretical, and practical implications are discussed.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".