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Record W3185433971 · doi:10.3389/feduc.2021.704135

Conceptualizing Thriving: An Exploration of Students’ Perceptions of Positive Functioning Within Graduate Education

2021· article· en· W3185433971 on OpenAlexaffabout
Heather Coe-Nesbitt, Eleftherios Soleas, Anoushka Moucessian, Nadia Arghash, Benjamin Kutsyuruba

Bibliographic record

VenueFrontiers in Education · 2021
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsQueen's University
Fundersnot available
KeywordsThrivingConstruct (python library)PsychologyPerceptionGraduate studentsMedical educationCurriculumPedagogyMedicineComputer science

Abstract

fetched live from OpenAlex

The current wellness crisis among graduate students calls on institutions of higher education to act and advocate for student thriving. While existing research on human thriving provides insight into how this experience of positive functioning can be understood across the lifespan, what it means to thrive within graduate programs—and by extension, how to support students in their ability to thrive within these programs—remains understudied. To address this gap in the literature, this study examined how graduate students describe and understand thriving within their programs of study. We thematically and quantitatively analyzed 2,287 Canadian graduate students survey responses to the question “How would you describe a student who is thriving in your program.” Findings indicate that graduate students conceptualize thriving as a complex and multi-dimensional construct involving both academic and non-academic components. The six overarching themes of achieving, engaging, connecting, balancing, enjoying, and being provide foundation for further exploration and insight into the ways that universities and post-secondary institutions can support students’ positive functioning.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.065
GPT teacher head0.435
Teacher spread0.369 · 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 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

Citations9
Published2021
Admission routes2
Has abstractyes

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