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Record W4406642532 · doi:10.54097/3hxcex38

A Review of “Double Reduction” Policy and “Family Educational Anxiety”: relationship and the distraction of Policy

2024· review· en· W4406642532 on OpenAlexaff
Ziming Yang

Bibliographic record

VenueJournal of Education Humanities and Social Sciences · 2024
Typereview
Languageen
FieldSocial Sciences
TopicGlobal Educational Reforms and Inequalities
Canadian institutionsTrinity Western UniversityWestern University
Fundersnot available
KeywordsDistractionAnxietyReduction (mathematics)PsychologyCognitive psychologyPsychiatryMathematics

Abstract

fetched live from OpenAlex

Educational burden and educational anxiety have been obsessed with Chinese families for an extended period. The Central Committee of Central China has further announced the “Double Reduction” policy to reduce the pressure on new generations and Chinese families. The policy has an unprecedented impact on all educational institutions, both public and outside tutoring institutions. Even though the policy is determined to relieve student pressure, the pressure remains. The ignorance of family education and the relationship between the policy and the inherent mindset of parents are essential factors dragging the policy down. The paper is dedicated to reviewing the existing contributions and analyzing how family factors are conducive to the policy. Focusing on the undergoing policy circumstances, lost sight of family education, and parental mindset of children’s life and grades.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.006
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
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 head0.191
GPT teacher head0.482
Teacher spread0.291 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2024
Admission routes1
Has abstractyes

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