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Record W3096862865 · doi:10.1177/1077800420962477

Massive and Microscopic Sensemaking During COVID-19 Times

2020· article· en· W3096862865 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

VenueQualitative Inquiry · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAutoethnographySensemakingPerspective (graphical)Coronavirus disease 2019 (COVID-19)SociologyEvent (particle physics)Power (physics)Scale (ratio)EthnographyPandemicQualitative researchPsychologyAestheticsEpistemologyPublic relationsGender studiesVisual artsSocial scienceMedicinePolitical scienceArt

Abstract

fetched live from OpenAlex

How does this pandemic moment help us to think about the relationships between self and other, or between humans and the planet? How are people making sense of COVID-19 in their everyday lives, both as a local and intimate occurrence with microscopic properties, and a planetary-scale event with potentially massive outcomes? In this paper we describe our approach to a large-scale, still-ongoing experiment involving more than 150 people from 26 countries. Grounded in autoethnography practice and critical pedagogy, we offered 21 days of self guided prompts to for us and the other participants to explore their own lived experience. Our project illustrates the power of applying a feminist perspective and an ethic of care to engage in open ended collaboration during times of globally-felt trauma.

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)0.003
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
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 head0.798
GPT teacher head0.712
Teacher spread0.086 · 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