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Record W3181049741 · doi:10.1080/03634523.2021.1948084

Same storm, different nightmares: emergency remote teaching by contingent communication instructors during the pandemic

2021· article· en· W3181049741 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

VenueCommunication Education · 2021
Typearticle
Languageen
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAutoethnographyResistance (ecology)ScholarshipPandemicPublic relationsSociologyPsychologyPolitical scienceCoronavirus disease 2019 (COVID-19)MedicineGender studiesLaw

Abstract

fetched live from OpenAlex

The COVID-19 pandemic amplified existing inequities in higher education. This paper documents the stories of four precariously employed communication instructors in their transition to emergency remote teaching in March 2020. Through collaborative autoethnography, the instructors share their stories of reliance and compliance within the gig academy, using their support networks to foster resilience and create points of resistance. In the Spring 2020 semester, we experienced the same storm but with different nightmares. Technological frustrations, mental health concerns, accent barriers, financial stresses, care work, and illness were pushed to the background while we dealt with suddenly teaching online during the pandemic. The relentless uncertainty about job security hanging overhead persists. From our subaltern counterpublic, we posit a resistance to the gig academy. We urge departmental leadership to use this paper to inform policy making and practice and for other contingent instructors to expose their stories in scholarship.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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 score0.268
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.037
GPT teacher head0.389
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