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Record W4317039726 · doi:10.51357/jdll.v2i2.204

University is Not for the Weak: Student Communication of Mental Health on Twitter

2023· article· en· W4317039726 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Digital Life and Learning · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsMental healthFeelingAnxietyPsychologyMedical educationCoronavirus disease 2019 (COVID-19)Depression (economics)Face (sociological concept)PandemicPsychiatryMedicineSocial psychologySociology

Abstract

fetched live from OpenAlex

Well before the COVID-19 pandemic exacerbated postsecondary students' mental health challenges, students were already struggling with issues that were pervasive in higher education, including anxiety, depression, overwhelm, burnout, and difficulty accessing mental health supports. This paper examines 1007 Twitter posts pertaining to higher education students' mental health between February 2019 and March 2021. Students expressed feelings that their institutions did not care about sound mental health and that higher education is an environment primed for anxiety and depression. Students also expressed a desire for timely, online counselling and closer contact and communication with their instructors. Online/virtual therapy/counselling was particularly valuable for students, and they appreciated accommodations that faculty made for them during the pandemic. Students also used Twitter to offer support and encouragement to one another. This study has implications for pedagogical developments and revisions to mental health supports available to college and university students in both online and face-to-face environments.

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)0.001
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 score0.300
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.048
GPT teacher head0.356
Teacher spread0.308 · 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