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Record W3122410466 · doi:10.1186/s41018-020-00089-x

Politics of citizenship during the COVID-19 pandemic: what can educators do?

2021· article· en· W3122410466 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.

Bibliographic record

VenueJournal of International Humanitarian Action · 2021
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsConcordia University
Fundersnot available
KeywordsCitizenshipPandemicCoronavirus disease 2019 (COVID-19)PoliticsPolitical science2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)International relationsHuman rightsLawVirologyMedicinePathology

Abstract

fetched live from OpenAlex

As a once in a 100 years emergency, the COVID-19 pandemic has resulted in repercussions for the economy, the polity, and the social. Also, the ongoing pandemic is as much a teaching moment as it to reflect on the lack of critical citizenship education. The fault lines of the health system have become visible in terms of infection and death rates; the fault lines of the educational system are now apparent in the behavior of the citizens who are flouting the public health guidelines and, in certain cases, actively opposing these guidelines. The main objective of this commentary is to initiate a dialogue on the social contract between the state and the subjects and to see how education and educators can respond to the challenge of the new normal. It is contended that education under the new normal cannot afford to keep educating for unbridled productivity education under the new normal. It must have welfare, human connections, ethical relationships, environmental stewardship, and social justice front and center.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.091
GPT teacher head0.432
Teacher spread0.341 · 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