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Record W4310251593 · doi:10.1386/peet_00048_1

Performing in the pandemic: The COVID-19 chronicles of Asian mother artists

2022· article· en· W4310251593 on OpenAlexaboutno aff
Ruchika Wason Singh

Bibliographic record

VenuePerforming Ethos International Journal of Ethics in Theatre and Performance · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)CuriosityNarrativeCoping (psychology)ChinaIdentity (music)StudioPsychologySociologyGender studiesHistoryAestheticsSocial psychologyVisual artsMedicineArtLiteratureDisease

Abstract

fetched live from OpenAlex

This article seeks to collect stories and make heard the voices of mother artists of Asian descent/Asia, about their experiences during the COVID-19 pandemic. The focus is on documenting the implications of their experiences during the pandemic, on their maternal role performance and their studio practice. Some of the points of departure proposed to the artists include disruptions in routines, re-prioritization of work, changes in durational attention given to the work before the pandemic, the psychological and physiological impact of the pandemic on individual health to impede role performance, and the impact of the challenges/changes on the sense of self/identity. At the same time there is also a curiosity about the coping mechanisms they might have sought to counter the situations. I have curated the collection of narratives by inviting Phaptawan Suwannakudt (Australia and Thailand), Nidhi Agarwal (India), Monika Lin (China and United States), Tazeen Qayyum (Canada and Pakistan) and Arisa Chinen (Japan) to share their stories. Their artistic responses will be in the form of text and image.

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 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)0.006
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.130
GPT teacher head0.379
Teacher spread0.248 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2022
Admission routes1
Has abstractyes

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