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Record W4409611154 · doi:10.5430/jct.v14n2p73

The Future of Education in the United States: Emulating the Billion Oyster Curriculum and Community Environmental Restoration Science (STEM + Computer Science) for Secondary School Success

2025· article· en· W4409611154 on OpenAlexvenueno aff
Lauren Birney, D. McNamara

Bibliographic record

VenueJournal of Curriculum and Teaching · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumScience educationOysterMathematics educationEnvironmental educationSociologyPedagogyPsychologyEcologyBiology

Abstract

fetched live from OpenAlex

Recent educational developments on the national and regional scale have called for a radical transformation. New York State is reassessing the qualifications needed for high school students to attain a diploma. The federal government is threatening to abolish the United States Department of Education. For students to be prepared to face the challenges of the global economic landscape, several 21st-century skills will be needed. The Billion Oyster Curriculum and Community Environmental Restoration Science (STEM + Computer Science) offers a multifaceted, content-rich, community problem-based model that provides a pattern for similar community involvement while incorporating the competencies and skills needed to become successful in higher education and employment. Student exposure and confidence in STEM content and computational skills enhance their awareness of this as a possible career choice. A student survey which contains a confidence in technological abilities subscale was administered to all subjects of this study.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.282
Teacher spread0.268 · 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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