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Record W7045807996

“The Brain Melt Is Real”: On Student and Instructor Notions of Digital Technology-Induced Distractedness at McMaster University

2024· dissertation· en· W7045807996 on OpenAlexafffund

Bibliographic record

VenueMacSphere (McMaster University) · 2024
Typedissertation
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsPerceptionDigital nativeDistractionEmerging technologiesTechnological literacyDigital scholarship
DOInot available

Abstract

fetched live from OpenAlex

This thesis examines the rapid expansion of the ‘discourse of distraction,’ which I define as a widespread public perception that students who grew up with access to digital activities are unable to concentrate on academic tasks, and, that such activities in adulthood are distracting. Based on a literature review and semi-structured interviews with Social Sciences undergraduate students and faculty at McMaster University, I argue that the contemporary socio-political environment of universities has facilitated the utilization of digital technologies in a manner which is harmful students’ ability to concentrate. I also argue that digital technologies impact various socio-cultural dimensions of the university. Finally, I suggest that the discourse of distraction has sufficient force to change how people interact with digital technology and schoolwork altogether.

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)0.007
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0150.039
Scholarly communication0.0160.007
Open science0.0030.012
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.263
Teacher spread0.249 · 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 designQualitative
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 routes2
Has abstractyes

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