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Record W3195611834 · doi:10.22329/jtl.v15i2.6725

Building a Plane While Flying

2021· article· en· W3195611834 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Teaching and Learning · 2021
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsYork University
Fundersnot available
KeywordsContext (archaeology)MetaphorPublic relationsChristian ministryPoliticsCoronavirus disease 2019 (COVID-19)Political scienceSociologyPublic policyPandemicPedagogyMedicineGeography

Abstract

fetched live from OpenAlex

We use the metaphor of building a plane while flying to describe the enactment of educational policies by teachers during COVID-19 and the impact of these policies on their ability to meet the needs of their students. Drawing from a series of three one-hour focus groups with seven teachers in Alberta, we apply critical policy analysis to describe the transition of public schools to pandemic education, especially in urban centers. This paper will begin by reviewing the dynamic policy context of school closures and reentry strategies and proceed to outline the diverse ways school boards interpreted guidelines from the Ministry of Education. We discuss the frustration with and variation of policy enactment during the pandemic, especially with respect to priorities and barriers to addressing student wellbeing and access to educational and social supports. Finally, we describe the consequences of teaching through crisis as it emerges in a political context that has failed to respond to educator’s professional needs.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.900
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.058
GPT teacher head0.411
Teacher spread0.353 · 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