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Record W2594199692 · doi:10.1145/3020165.3022158

Do Highlights Affect Comprehension?

2017· article· en· W2594199692 on OpenAlexaff
Samuel Dodson, Luanne Freund, Rick Kopak

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComprehensionReading comprehensionAffect (linguistics)Reading (process)Cognitive styleComputer scienceField (mathematics)Cognitive psychologyIndependence (probability theory)CognitionStyle (visual arts)Process (computing)PsychologyLinguisticsCommunicationMathematics

Abstract

fetched live from OpenAlex

A largely unquestioned assumption in social reading is that publicly shared annotations improve reading outcomes. In this study, we explore the specific assumption that relevant and irrelevant passive highlighting affects comprehension. Participants were divided by cognitive style based on their degree of Field Dependence-Independence [20]. We found that irrelevant highlights had significant negative effects on reading comprehension for Field Independents (FIs), but not Field Dependents (FDs). This is a surprising result because FDs typically rely on external cues to structure and help process information, whereas FIs use internal cues. This suggests that highlighting cues information but does not structure it.

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 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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.002

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 head0.109
GPT teacher head0.330
Teacher spread0.221 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations3
Published2017
Admission routes1
Has abstractyes

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