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Record W6902262586 · doi:10.60770/r1jt-b487

The mere presence of a cell phone and academic ability

2024· article· en· W6902262586 on OpenAlexaff

Bibliographic record

VenueMount Royal University Institutional Repository (Mount Royal University) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsMount Royal University
Fundersnot available
KeywordsPhoneSpellingSentenceAffect (linguistics)ComprehensionTest (biology)Cognition

Abstract

fetched live from OpenAlex

Prior research has suggested that cell-phone use in the classroom and during learningrelated tasks is detrimental to academic performance. Recently, the mere presence of a cell phone has been found to negatively affect relationships and to impair performance on learning and cognitive tasks. The present study explored whether the presence of a cell phone hinders performance on tests that measure pre-existing academic ability. In total, the study evaluated 45 participants who were enrolled in an introductory psychology course at Mount Royal University or who were members of the general public. Three subtests from the Wide Range Achievement Test (WRAT-4) were completed: spelling, sentence comprehension, and mathematics. During testing, half of the participants had their cell phones present and the other half did not. Statistical analyses revealed that when a cell phone belonging to a participant was merely present, there was no statistically significant difference in the demonstration of pre-existing skills on the sentence comprehension (p = .52), spelling (p = .07), and mathematics subtest (p = .11) compared to when a cell phone was removed. Unexpectedly, a non-significant trend was observed in the opposite direction; that is, the cell-phone-present group outperformed the cell-phone-absent group on all of the subtests.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.010
GPT teacher head0.227
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), 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
Published2024
Admission routes1
Has abstractyes

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