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Record W4391220681 · doi:10.1037/cep0000323

Looks can be deceiving: Investigating change blindness in an online setting.

2024· article· en· W4391220681 on OpenAlexafffund
Saeeda Saeed, Arianna Cook, Victoria Mackie, Dana A. Hayward

Bibliographic record

VenueCanadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsUniversity of AlbertaUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaLaidlaw Foundation
KeywordsBlindnessChange blindnessPsychologyInternet privacyOptometryComputer scienceMedicineNeuroscienceCognition

Abstract

fetched live from OpenAlex

= 134), participants engaged in an online video chat with a confederate, with two levels of visual clutter (none, a lot) and three levels of interaction (none, light conversations about weather/TV, deeper conversations about goals/greatest regrets). We found no modulation of change blindness rates across perceptual clutter. Curiously, we found a large discrepancy in change blindness rates in Experiment 1 (79%; 52/66) versus Experiment 2 (16%; 11/68) that we explored, leading to some evidence that increasing the level of interaction led to greater change blindness rates, but only for pairs who identified as belonging to different ethnicities. Taken together, our work suggests that we may pay attention to people differently in virtual settings compared to in-person, that in-group and out-group biases may have an effect on change blindness rates, and that while clutter does not seem to affect change blindness rates, one's level of interaction just might. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.207
GPT teacher head0.403
Teacher spread0.196 · 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 teacher head, not a consensus.

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

Citations1
Published2024
Admission routes2
Has abstractyes

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