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Record W4404010686 · doi:10.1038/s44271-024-00155-9

People are increasingly bored in our digital age

2024· review· en· W4404010686 on OpenAlex
Katy Y. Y. Tam, Michael Inzlicht

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

VenueCommunications Psychology · 2024
Typereview
Languageen
FieldNeuroscience
TopicMind wandering and attention
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

In an era where entertainment is effortlessly at our fingertips, one would assume that people are less bored than ever. Yet, reports of boredom are higher now than compared to the past. This rising trend is concerning because chronic boredom can undermine well-being, learning, and behaviour. Understanding why this is happening is crucial to prevent further negative impacts. In this Perspective, we explore one possible reason—digital media use makes people more bored. We propose that digital media increases boredom through dividing attention, elevating desired level of engagement, reducing sense of meaning, heightening opportunity costs, and serving as an ineffective boredom coping strategy. In recent years, there has been an increase in both reports of boredom and greater use of digital media. Digital media may exacerbate boredom via multiple pathways including dividing attention and reducing sense of meaning.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.252
GPT teacher head0.477
Teacher spread0.226 · 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