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Record W2946763696 · doi:10.22230/ijepl.2019v15n6a821

Fostering a Culture of Innovation: A Case Study of Elementary School Principals in Costa Rica

2019· article· en· W2946763696 on OpenAlexvenueno aff
Miguel M. Gonzales, Richard Storti

Bibliographic record

VenueInternational Journal of Education Policy and Leadership · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChristian ministryDecreePolitical scienceExecutive directorPublic administrationPrimary educationPublic relationsSociologyManagementPedagogyEconomics

Abstract

fetched live from OpenAlex

To help promote a culture of innovation, the Ministry of Education andthe Ministry of Science, Technology, and Telecommunication of Costa Rica estab-lished a national executive decree requiring all public schools in the country partic-ipate in the National Program of Science and Technology Fairs (NPSTF). This casestudy examines the role of five elementary school principals in Costa Rica in implementing and preparing their schools for the NPSTF initiative. Principals played threesignificant roles: the motivator of teachers and students; acquirer of NPSTF resources;and the organizer of NPSTF committees and coalitions to help train and finance theinitiative. It is recommended the Ministry of Education establish a budget solely ded-icated to support infrastructure and professional development for NPSTF while aligning goals with all stakeholders.

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)0.005
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0190.007
Scholarly communication0.0070.002
Open science0.0020.006
Research integrity0.0020.003
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 head0.211
GPT teacher head0.386
Teacher spread0.175 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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