Through a Rear-View Mirror: Families Look Back at a Family Literacy Program
Bibliographic record
Abstract
In this article, we report on a study in which we interviewed working class families who were the first cohort in a family literacy program that had been locally developed and implemented in a small village in Canada more than two decades previously in response to community-identified needs. The study was framed by Tulving’s concept of episodic memory which he described as autobiographical and which allows one to recall and reflect on one’s past experiences because they are significant. Ten of the original 18 families were available, and they were interviewed in their homes using a semi-structured protocol. Interviews were transcribed and then coded according to themes. Findings include the following: families reported that the hands-on structure of the program in which they worked alongside their children helped them understand learning through play and developmentally appropriate curriculum and pedagogy; they gained insights as to how they could continue to support their children’s learning at home and in the community; they became more comfortable in school and knowledgeable about its workings and subsequently participated more in school affairs; they and their children benefited socially from the program; and they believed the program assisted their children’s transition to school. They also identified areas that needed improvement, including more frequent ses sions and more explanation of some aspects of the program. The study extends previous research in family literacy in that it demonstrates that programs can contribute to families’ social capital.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".