MétaCan
Menu
Back to cohort
Record W3174309292 · doi:10.1080/02568543.2021.1930823

Going Beyond: Implementing “Beyond Quality” through the Investigating Quality (IQ) Project

2021· article· en· W3174309292 on OpenAlexaffabout
Alan Pence

Bibliographic record

VenueJournal of Research in Childhood Education · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAotearoaEarly childhood educationIndigenousEarly childhoodGovernment (linguistics)Political scienceEquity (law)PedagogySociologyPublic administrationPsychologyGender studies

Abstract

fetched live from OpenAlex

The Investigating Quality (IQ) Project was conceptualized as a multiple systems approach to transforming early childhood education, care, and development (ECE/ECD) in British Columbia, Canada. Those systems extended from provincial government to local programs, from innovative policies to new approaches to practice. Fortunately, the tenure of the IQ project (16 years in 2021) allowed time for research and scholarly work to take place that ranged from comparative policy analysis to analyses of frontline practice authored by practitioners as well as academics, and from innovations in ECE post-secondary education to the study of environmental and equity issues within the Anthropocene. The IQ project’s publication outlets included international scholarly journals as well as provincial and national ECE association journals. Among the scholarly works were many that commenced as master’s theses and doctoral dissertations, themselves opening up new avenues of study. While key inspirations for the IQ Project (including Indigenous initiatives in Canada) predate and lie outside the initial, early 1990s foci of the U.S.-initiated ECE Reconceptualist movement (RECE), later international RECE, as well as Reggio-Emilia, Swedish/Reggio, and Aotearoa/New Zealand Te Whariki scholarly literatures, are kindred spirits for IQ articles, chapters, and books.

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)0.024
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.190
GPT teacher head0.535
Teacher spread0.345 · 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 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

Citations3
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Research in Childhood EducationSame topicEarly Childhood Education and DevelopmentFrench-language works237,207