MétaCan
Menu
Back to cohort
Record W3059508327 · doi:10.5430/jct.v9n3p76

The Canary in the Mine: Remote Learning in the Time of COVID-19

2020· article· en· W3059508327 on OpenAlexvenueno aff
David C. Coker

Bibliographic record

VenueJournal of Curriculum and Teaching · 2020
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsOperationalizationStaffingCurriculumCoronavirus disease 2019 (COVID-19)Political scienceEquity (law)BusinessPublic relationsPsychologyPedagogyMedicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

National organizations in the United States issued policy proposals for returning to school during the COVID-19 pandemic. A qualitative review, using the constant comparison model, examined six policies from different organizations. The policies operate on the notion of a progressive curriculum, with the values of equity, access, and adaptations driving the planning process. There are five variables national policies utilize to operationalize the progressive curriculum and values: organizing, staffing, scheduling, envisioning, and vulnerabilities. A case study using an individual school district examined the impact on learning within the framework of the policies. Recommendations to improve online and remote learning follow.

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)0.007
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.007
Scholarly communication0.0050.011
Open science0.0020.007
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.038
GPT teacher head0.385
Teacher spread0.347 · 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 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

Citations22
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Curriculum and TeachingSame topicCOVID-19 and Mental HealthFrench-language works237,207