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Record W4308145989 · doi:10.1080/00909882.2022.2140595

Dialogues for equity: precarious parent-scholars in times of crisis

2022· article· en· W4308145989 on OpenAlexaff
Anis Rahman, Nicole K. Stewart, Betty Ackah, Byron Hauck

Bibliographic record

VenueJournal of Applied Communication Research · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsSimon Fraser UniversityUniversity of the Fraser Valley
Fundersnot available
KeywordsAutoethnographyPrecarityEquity (law)SociologyNeoliberalism (international relations)NegotiationPrecarious workInterdependenceGender studiesPandemicWork (physics)Public relationsPolitical scienceCoronavirus disease 2019 (COVID-19)Social science

Abstract

fetched live from OpenAlex

The COVID-19 pandemic amplified inequities around parent-scholars in the neoliberal gig academy. This paper documents the stories and intersectional struggles of four precarious parent-scholars as they navigated doctoral work, dissertation defenses, research, remote teaching, and family life during the pandemic. We illustrate how we navigated our neoliberal subjectivities and the extending multifold crises around the division of labor between academic work and parenting, gender roles, and internalized pressures exacerbated by a public postsecondary education system that exploits increasingly precarious workforces. Through critical collaborative autoethnography, we reflect on our parenting and teaching from March 2020 to August 2021. Drawing from our collective findings we summarize three mutually interdependent areas of communicative intervention that can make our workplace more equitable, entailing self-reflection, negotiation of labor, and collaborative dialogue.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.025
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.036
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0290.056
Scholarly communication0.0160.014
Open science0.0030.029
Research integrity0.0050.011
Insufficient payload (model declined to judge)0.0040.000

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 head0.352
GPT teacher head0.525
Teacher spread0.172 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2022
Admission routes1
Has abstractyes

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