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Record W4214741076 · doi:10.1177/01461672221077791

Anxiety, Cognitive Availability, and the Talisman Effect of Insurance

2022· article· en· W4214741076 on OpenAlexaff
Robert M. Schindler, Mathew S. Isaac, Eric Dolansky, Grant C. Adams

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsBrock University
Fundersnot available
KeywordsPsychologyAnxietyCognitionSocial psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

of insurance-consumers who have an insurance policy feel that the covered mishap is less likely to occur. Although such an effect has previously been proposed, empirical evidence for it is limited, in part because the talisman effect has often been conflated with a related but distinct magical-thinking phenomenon, the tempting-fate effect. By disentangling these two effects, we are better able to isolate the talisman effect and show that it is a robust phenomenon in its own right. We also provide support for a mechanism underlying the talisman effect: Insurance reduces anxiety and repetitious thoughts related to the mishap; with fewer thoughts about the mishap, its cognitive availability is lower and so it seems less likely to occur.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.529
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.071
GPT teacher head0.401
Teacher spread0.330 · 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 designObservational
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

Citations2
Published2022
Admission routes1
Has abstractyes

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