MétaCan
Menu
Back to cohort
Record W4384347878 · doi:10.55849/wp.v1i1.54

Student Stress Levels in Academic Learning During the Covid-19 Pandemic

2022· article· en· W4384347878 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

VenueWorld Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicStudent Stress and Coping
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Stress (linguistics)PsychologyCognitionMathematics educationReliability (semiconductor)2019-20 coronavirus outbreakDevelopmental psychologyMedicineVirologyOutbreakPsychiatry

Abstract

fetched live from OpenAlex

This study aims to determine the level of stress of junior high school students in learning during the Covid-19 pandemic in Nagari Pangian, Lintau Buo District. The type of research used is quantitative descriptive research. The confession of reliability is 0.96,4, with a total of 60 items covering four psychological, physiological, cognitive, and behavioral factors. There are four choices of stress levels in selecting categories in collecting data: strongly agree, agree, degrees during, and strongly disagree. The level of the stress of junior high school students in academic learning during the Covid-19 pandemic was in the high category, where 30 subjects (22.7%) were at moderate stress levels, 63 subjects (47.7%) were at high-stress levels, and 39 subjects (29.5%) were at very high-stress levels.

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 categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0120.000

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 head0.132
GPT teacher head0.472
Teacher spread0.340 · 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