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Record W4414402540 · doi:10.22215/cujs.v5i2.5302

Exploring Academic Resilience Among Young Canadian Adults

2025· article· en· W4414402540 on OpenAlexaffabout
Daniel Sulatycky, Kathryne E. Dupré

Bibliographic record

VenueCarleton undergraduate journal of science. · 2025
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsCarleton University
Fundersnot available
KeywordsCuriosityLonelinessMental healthPsychological resilienceIntervention (counseling)Moderation

Abstract

fetched live from OpenAlex

This study examined the relationship between academic resilience and mental health, focusing on potential moderators in accordance with the Conservation of Resources (COR) theory. It was hypothesized that academic resilience would be positively associated with mental health, while epistemic curiosity and increased healthy lifestyle behaviours would attenuate this relationship. Conversely, it was expected that financial strain and loneliness would weaken the relationship. A total of 214 undergraduate psychology students participated in the study by completing an online survey addressing the relevant variables. Moderation analysis revealed that epistemic curiosity, financial strain, and health behaviours did not significantly enhance or abate the relationship between academic resilience and mental health. The remaining moderator, loneliness, did weaken the relationship between academic resilience and students’ mental health. Open-text responses further complimented these results, with social support arising as a key theme. These findings highlight the importance of early intervention for lonely students and emphasize identifying shared attributes among students for more targeted support and better outcomes.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.049
GPT teacher head0.360
Teacher spread0.311 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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