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Record W4221067523 · doi:10.1177/23780231221088438

The Age of Satisficing? Juggling Work, Education, and Competing Priorities during the COVID-19 Pandemic

2022· article· en· W4221067523 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSocius Sociological Research for a Dynamic World · 2022
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentGreater Texas Foundation
KeywordsLeverage (statistics)SatisficingPandemicQuarter (Canadian coin)Postsecondary educationHigher educationWork (physics)Coronavirus disease 2019 (COVID-19)Demographic economicsSociologyPsychologyPolitical sciencePublic relationsEconomic growthEconomicsInfectious disease (medical specialty)GeographyMedicineDisease

Abstract

fetched live from OpenAlex

The coronavirus disease 2019 pandemic continues to shape individuals' decisions about employment and postsecondary education. The authors leverage data from a longitudinal qualitative study of educational trajectories to examine how individuals responded to the shifting landscape of work and education. In the final wave of interviews with 56 individuals who started their postsecondary education at a community college 6 years ago, the authors found that most respondents described engaging in satisficing behaviors, making trade-offs to maintain their prepandemic trajectories where possible. More than a quarter of individuals, primarily those with access to fewer resources, described trajectories fraught with insecurity; they struggled to juggle competing obligations, especially in the face of an unpredictable labor market. A small portion of participants described making optimizing decisions, which were sometimes risky, to prioritize their aspirations. These descriptive patterns may partially explain mechanisms shaping recent shifts in employment and postsecondary education, including lower labor-market engagement and declines in college enrollment.

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)0.009
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.559
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0170.002
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.236
GPT teacher head0.532
Teacher spread0.296 · 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