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Striving for Sustainable Development: Analysis of the Revenue and Operation Cost of Private Kindergartens in Chinese Society

2023· preprint· en· W4319460258 on OpenAlexaff
Jing Gao, Hailan Wang, Yue Shao, Yaqin Duan, Wei Wang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsRevenueProfitability indexBusinessSustainable developmentChinaFinanceTotal revenueQuestionnaireGeography

Abstract

fetched live from OpenAlex

This study explores the revenue and operation cost structures of private kindergartens in China as profitability is key to their sustainable development. Altogether 233 private kindergartens were sampled and involved in the survey study, which provides a quantitative analysis of the researcher-designed Questionnaire on the Revenue and Cost of Private Kindergartens (QRCPK). And 23 of these participating kindergartens were involved in a semi-structured interview. Analyses of both survey and interview data jointly indicated that: (1) the majority of the revenue of private kindergartens depended on the tuition fees; (2) their labor cost and rent costs are massive high; (3) the low profitability has been proved by the high cost-revenue ratio; (4) the poor cost accounting and financial management strategies hindered the sustainable development of private kindergartens.

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)0.000
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.214

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.031
GPT teacher head0.334
Teacher spread0.303 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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