An exploration of the post-pandemic profiles and predictors of children’s digital literacy and multimodal practices in Canada
Bibliographic record
Abstract
With children’s digital technology usage surging in post-pandemic Canada, it is imperative to understand children’s digital literacy and multimodal practices. This study investigated potential predictors of children’s digital literacy and multimodal practices at home, and the latent profiles of digital families. A sample of 413 parents of children aged 0–8 was recruited online and from daycare centres in Central Ontario to examine children’s home digital environments, digital literacy, and multimodal practices. The findings indicated that (1) child age, home digital resources, and parent’s beliefs regarding child digital technology use predicted increased digital literacy and multimodal practices. (2) Three profiles of digital families were identified: low-digital families (36.9%), moderate-digital families (51.2%), and high-digital families (11.9%). Our research sheds light on the digital landscape of Canadian families with young children and suggests financial status may not be the primary factor in identifying children who can benefit from initiatives supporting digital literacy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".