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Record W3208299040 · doi:10.1177/21582440211046943

Family-Focused Early Learning Programing: Access, Opportunities, and Issues in one Canadian Context

2021· article· en· W3208299040 on OpenAlexaffabout
Antoinette Doyle, Ling Li

Bibliographic record

VenueSAGE Open · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsFacilitatorContext (archaeology)Family literacyLiteracyPublic relationsMedical educationPsychologyPedagogyPolitical scienceMedicineSocial psychologyGeography

Abstract

fetched live from OpenAlex

Family-focused early learning programs aim to assist parents in supporting their young children language and literacy development. This study examined program access and learning opportunities for diverse families across a wide range of community-based settings in one eastern Canadian province. As well, the study examined practitioners’ perspectives on issues related to program development and implementation. Primarily through surveys, practitioners provided data on more half of all community-based programs in the province. The findings of the study showed that most programs offered a form of parent and child focused drop-in play as the core of their programing. Few programs offered a more formalized parent-facilitator learning component as is sometimes found in other jurisdictions. The issues and challenges in programing identified by practitioners included attracting participants, maintaining funding and expanding program activities, and staff training to expand and enhance programing to meet the needs of families. These issues are discussed in light of current public policy and practice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.863

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0270.004
Scholarly communication0.0050.001
Open science0.0030.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.248
GPT teacher head0.399
Teacher spread0.151 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes2
Has abstractyes

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