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Record W2766439719

Context effects in explanation evaluation - eScholarship

2014· article· en· W2766439719 on OpenAlexaboutno aff
Nadya Vasilyeva, John D. Coley

Bibliographic record

VenueProceedings of the Annual Meeting of the Cognitive Science Society · 2014
Typearticle
Languageen
FieldComputer Science
TopicTopic Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsCounterintuitiveNarrativeRecallContext (archaeology)PsychologyPlot (graphics)CognitionSocial psychologyCognitive psychologyEpistemologyHistoryLiteratureArtPhilosophyMathematics
DOInot available

Abstract

fetched live from OpenAlex

Does Narrative Transportation Facilitate Memory for Counterintuitive Concepts? M. Afzal Upal Leader of Effects & Influence Research Group Defence R & D Canada Toronto Abstract: A series of studies carried out over the last two decades have shown that those people who allow themselves to be immersed in a story are more likely to experience its persuasive effects (Green, Sasota & Jones 2010). A number of studies carried out by cognitive scientists of religion have shown that people better remember counterintuitive ideas embedded in stories (Upal et al. 2007). This paper reports on a study carried out to test the hypothesis that narrative transportation facilitates memory for counterintuitive concepts i.e., more someone is transported into a story, the better memory they will have for counterintuitive concepts embedded in the story. Participants read 3 stories (each containing 6 counterintuitive concepts) with different narrative transportation levels and completed the narrative transportation scale. Responses were coded for recall. The results were mixed with the transportation facilitating recall but only for concepts that were critical to the story plot.

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)0.009
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.276
Teacher spread0.255 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2014
Admission routes1
Has abstractyes

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