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Record W4416425582 · doi:10.1177/14639491251389614

Bridging the research–practice divide in exploring early childhood education quality

2025· article· en· W4416425582 on OpenAlexaff
Mengran Liu, Alfredo Bautista

Bibliographic record

VenueContemporary Issues in Early Childhood · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsBridging (networking)Early childhood educationPositivismSituatedChinaConstruct (python library)Quality (philosophy)

Abstract

fetched live from OpenAlex

Drawing on a growing body of international literature that conceptualises early childhood education (ECE) quality as a culturally constructed rather than a universal notion, this colloquium discusses how quality is being investigated in China, a country where ECE research has grown exponentially in recent years. The colloquium is structured into two main sections, highlighting the differing approaches to quality inquiry among Chinese academic researchers and practitioners, respectively. Whilst many Chinese academic researchers still adopt positivist paradigms, viewing quality as an objective reality, they extend frameworks by developing localised quality standards that foreground cultural considerations. Researchers’ work is often published in high-impact English-language journals, reflecting their engagement with global discourses whilst addressing Chinese contextual specificities. In contrast, Chinese ECE practitioners employ methods that transcend positivism through action research, commentaries and reflective papers. Some practitioner-led explorations offer nuanced, practice-informed, locally situated perspectives to construct ECE quality. However, practitioners’ views are mainly published in Chinese lower-tier journals with limited international visibility. We argue that academic researchers and practitioners select divergent paradigms and methods to investigate ECE quality, producing different types of knowledge. Lack of collaboration among them may lead to fragmented definitions, hindering coherent improvement of ECE practices. A critical next step would involve integrating Chinese researchers’ and practitioners’ perspectives more rigorously to conceptualise the multifaceted and context-specific nature of ECE quality. Insights gained from China can inform international dialogues about ECE quality around the world.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.117
GPT teacher head0.420
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 teacher head, not a consensus.

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
Published2025
Admission routes1
Has abstractyes

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