The integration of affective characteristics of the family environment for a more comprehensive explanatory model of reading abilities
Bibliographic record
Abstract
Introduction This research focuses on the influence of familial affective characteristics on family literacy practices and children’s reading abilities. Parenting stress and educational practices were two affective characteristics of interest. Parenting stress is defined as a state of psychological discomfort specifically associated with the education of a child whereas educational practices are defined as various means the parent uses to educate and socialize the child. Methods A sample of 154 grade 1 children allowed for a correlational analysis between parenting stress, educational practices, the frequency of family reading activities, the diversity of literacy material available and the type of child-parent exchange (alphabet-focus or story-focus). Regression analyses were conducted to develop a model predicting reading abilities. Results Three result outcomes are of interest for the field of reading development. First, our study establishes relations between educational practices and certain aspects of family literacy: diversity of supports, frequency of exchanges, and type of child-parent exchange and it suggests that parental engagement plays a significant role in various aspects related to at-home discussions about books. Second, our regression analysis highlights evidence that parenting stress is an explanatory factor directly linked to the child’s reading abilities. Therefore, our findings add reading abilities to the list of developmental aspects that is affected by parenting stress. Finally, the results show that, when parenting stress and educational practices are integrated in the predictive model, the story-focus exchanges remain predictive of reading abilities but not the alphabet-focus exchanges. Discussion Our findings confirm that the benefit of parent–child exchange on reading abilities is dependent of conditions of the family environment in which these activities occur. These findings also lead us to question the value of making alphabet-focus exchanges, the cornerstone of some literacy programs in family settings. Our findings call for caution when implementing such programs in family context. In fact, activities involving conversation about the meaning of a text or the links between the text and the child’s everyday reality represent the only activities, in our study, that had a beneficial effect on reading abilities while remaining permeable to parenting stress.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.011 | 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".