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Record W3118711146 · doi:10.12973/eu-jer.10.1.175

The Bases of Montessori Pedagogy as a Facilitating factor for Child Development in Burkina Faso and Spain

2021· article· en· W3118711146 on OpenAlexfundno aff
Aida Macià-Gual, Laura Domingo Peñafiel

Bibliographic record

VenueEuropean Journal of Educational Research · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Methods and Practices
Canadian institutionsnot available
FundersUniversity of Victoria
KeywordsMontessori methodStyle (visual arts)PedagogyPsychologyLow incomeCognitive styleEconomic growthDevelopmental psychologyEarly childhood educationMathematics educationSociologyCognitionGeographySocioeconomics

Abstract

fetched live from OpenAlex

Education faces barriers all over the world, which sometimes makes it difficult to look after children’s rights and their individual development. Hence, society is clamoring for new practices, and different approaches are emerging, Montessori among them. Despite the fact that this approach was developed to attend to the poor strata, nowadays it is basically promoted by elitist sectors, though it can be perfectly applied as an education system for all children, regardless of their socio-economic and cultural backgrounds. This study analyzes the bases of Montessori pedagogy in a school from a low-to-middle-income country (LMIC), Burkina Faso, and another school in a high-income country (HIC), Spain. The study takes into account children, family, school environment and teacher training all of which contribute to children’s development.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.267
GPT teacher head0.550
Teacher spread0.284 · 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 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

Citations7
Published2021
Admission routes1
Has abstractyes

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