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Record W3127201885 · doi:10.29173/iasl7595

Home-school Partnership

2021· article· en· W3127201885 on OpenAlexvenueno aff
Jacqueline Shek

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipReading (process)Reading aloudHome schoolPsychologyPedagogyMedical educationMathematics educationMedicinePolitical science

Abstract

fetched live from OpenAlex

Home-school partnership has been recognized as an important approach to promote student learning since the last century. Though families bear an inevitable role to teach reading at home, teachers and parent volunteers working together at school may motivate those students who are uninterested or less supported by their families to read. The interests of the current readers may also be strengthened. This paper presents a parent-child reading programme adopted in a Hong Kong primary school that engaged parent volunteers to read with the children in the morning. The objectives, the detailed plan and evaluation methods are discussed. After a year of implementation, the P.1 and P.2 students involved had remarkable improvements in various skills such as prediction skills, reading aloud and communication skills. Moreover, it served as a media to promote home-school partnership.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0030.002
Open science0.0010.009
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0360.005

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 head0.081
GPT teacher head0.355
Teacher spread0.274 · 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 designObservational
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 routes1
Has abstractyes

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