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Record W4379620035 · doi:10.1111/spc3.12754

The psychological benefit of future vividness in goal persistence: An illustrative case of the class of 2020 before & during COVID‐19

2023· article· en· W4379620035 on OpenAlexaboutno aff
Samantha L. McMichael, Virginia S. Y. Kwan

Bibliographic record

VenueSocial and Personality Psychology Compass · 2023
Typearticle
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsnot available
FundersInstitute of Education SciencesU.S. Department of Education
KeywordsGraduation (instrument)PsychologyPersistence (discontinuity)Socioeconomic statusCoronavirus disease 2019 (COVID-19)Quarter (Canadian coin)PandemicClass (philosophy)Graduate studentsDevelopmental psychologySocial psychologyMedical educationDemographyPedagogySociologyGeographyMedicine

Abstract

fetched live from OpenAlex

Abstract Graduating during COVID‐19, the Class of 2020 had difficulty pursuing their future goals. This research examined the likelihood of academic and career goal change early in the pandemic, disparities in persistence by socioeconomic status (SES), and how psychological resources mitigated goal change during the early stages of the pandemic. This 4‐year study surveyed students in the Class of 2020 eight times from their first week in college (Fall 2016) to their last semester before graduation (Spring 2020; N = 115; 20% below middle SES, 80% middle SES or above). Even in the first weeks of COVID‐19, a quarter of students changed goals. Lower SES students were less likely to persist in their post‐graduation plans. Nevertheless, students who entered college with a vivid image of their future were more likely to have secured a graduate school or job prospect prior to COVID‐19, and, in turn, were less likely to change goals.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.284
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.152
GPT teacher head0.454
Teacher spread0.303 · 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.

Study designObservational
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
Published2023
Admission routes1
Has abstractyes

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