MétaCan
Menu
Back to cohort
Record W1824379121 · doi:10.1177/1745691614545653

Registered Replication Report

2014· article· en· W1824379121 on OpenAlexaff
Victoria K. Alogna, Matthew K. Attaya, Philip Aucoin, Štěpán Bahník, Stacy Birch, Angela R. Birt, Brian H. Bornstein, Samantha Bouwmeester, Maria A. Brandimonte, Charity Brown, Karla Buswell, Curt A. Carlson, Maria A. Carlson, Simon Chu, Aleksandra Cisłak, M. Colarusso, Melissa F. Colloff, Kimberly S. Dellapaolera, Jean‐François Delvenne, Alberto Di Domenico, Aaron Drummond, Gerald Echterhoff, John E. Edlund, Casey Eggleston, Beth Fairfield, Gregory Franco, Bradlee W. Gamblin, Maryanne Garry, Richard J. Gentry, Elizabeth Gilbert, Daniel L. Greenberg, Jamin Halberstadt, Lauren C. Hall, Peter Hancock, Dale A. Hirsch, Glenys A. Holt, Jauhar Jackson, Jonathan Jong, Andre Kehn, Christopher Koch, René Kopietz, Ulrike Körner, Melina A. Kunar, Calvin K. Lai, Steve Langton, Fábio P. Leite, Nicola Mammarella, John E. Marsh, Kathleen A. McConnaughy, Shannon K. McCoy, Alex H. McIntyre, Christian A. Meissner, Robert B. Michael, Abigail A. Mitchell, Marino Mugayar-Baldocchi, Robin Musselman, Clayton Siu Fung Ng, Austin Nichols, Narina Nuñez, Matthew A. Palmer, Jessica Pappagianopoulos, Marilyn S. Petro, C. R. Poirier, Emma Portch, M. Rainsford, Arielle Rancourt, Connie J. Romig, Eva Rubínová, Mevagh Sanson, Liam Satchell, James D. Sauer, Kimberly Schweitzer, Judge David Shaheed, Faye Skelton, Griffin Sullivan, Kyle J. Susa, Jessica K. Swanner, W. Burt Thompson, Rachael Todaro, Joanna Ulatowska, Tim Valentine, Peter P. J. L. Verkoeijen, Marek Vranka, Kimberley A. Wade, Christopher A. Was, Dawn R. Weatherford, Kimberly D. Wiseman, Tara Zaksaite, Daniel V. Zuj, Rolf A. Zwaan

Bibliographic record

VenuePerspectives on Psychological Science · 2014
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsPsychologyTask (project management)Replication (statistics)Cognitive psychologyControl (management)Social psychologyArtificial intelligence

Abstract

fetched live from OpenAlex

Trying to remember something now typically improves your ability to remember it later. However, after watching a video of a simulated bank robbery, participants who verbally described the robber were 25% worse at identifying the robber in a lineup than were participants who instead listed U.S. states and capitals-this has been termed the "verbal overshadowing" effect (Schooler & Engstler-Schooler, 1990). More recent studies suggested that this effect might be substantially smaller than first reported. Given uncertainty about the effect size, the influence of this finding in the memory literature, and its practical importance for police procedures, we conducted two collections of preregistered direct replications (RRR1 and RRR2) that differed only in the order of the description task and a filler task. In RRR1, when the description task immediately followed the robbery, participants who provided a description were 4% less likely to select the robber than were those in the control condition. In RRR2, when the description was delayed by 20 min, they were 16% less likely to select the robber. These findings reveal a robust verbal overshadowing effect that is strongly influenced by the relative timing of the tasks. The discussion considers further implications of these replications for our understanding of verbal overshadowing.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Reproducibility · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptMetaresearch
Domain: Reproducibility · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.041
metaresearch head score (Gemma)0.194
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.778

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.194
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0070.010
Science and technology studies0.0060.003
Scholarly communication0.0080.004
Open science0.0050.005
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.4550.224

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 head0.116
GPT teacher head0.424
Teacher spread0.308 · 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

Labeled directly by 2 models reading the full record.

Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Other design
DomainReproducibility
GenreMethods · Empirical

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

Citations224
Published2014
Admission routes1
Has abstractyes

Explore more

Same venuePerspectives on Psychological ScienceSame topicMemory Processes and InfluencesCategoryMetaresearchFrench-language works237,207