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Record W2015778399 · doi:10.1037/a0036855

The psychology of martyrdom: Making the ultimate sacrifice in the name of a cause.

2014· article· en· W2015778399 on OpenAlexaff
Jocelyn J. Bélanger, Julie Caouette, Keren Sharvit, Michelle Dugas

Bibliographic record

VenueJournal of Personality and Social Psychology · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsCarleton UniversityUniversité du Québec à Montréal
Fundersnot available
KeywordsNomological networkPsychologySacrificeConceptualizationSocial psychologyTerrorismScale (ratio)MoralityCognitionSet (abstract data type)Cognitive psychologyEpistemology

Abstract

fetched live from OpenAlex

Martyrdom is defined as the psychological readiness to suffer and sacrifice one's life for a cause. An integrative set of 8 studies investigated the concept of martyrdom by creating a new tool to quantitatively assess individuals' propensity toward self-sacrifice. Studies 1A-1C consisted of psychometric work attesting to the scale's unidimensionality, internal consistency, and temporal stability while examining its nomological network. Studies 2A-2B focused on the scale's predictive validity, especially as it relates to extreme behaviors and suicidal terrorism. Studies 3-5 focused on the influence of self-sacrifice on automatic decision making, costly and altruistic behaviors, and morality judgments. Results involving more than 2,900 participants from different populations, including a terrorist sample, supported the proposed conceptualization of martyrdom and demonstrated its importance for a vast repertoire of cognitive, emotional, and behavioral phenomena. Implications and future directions for the psychology of terrorism are discussed.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.596
Threshold uncertainty score0.740

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
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 science0.0010.000
Research integrity0.0000.001
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 head0.074
GPT teacher head0.436
Teacher spread0.362 · 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 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

Citations102
Published2014
Admission routes1
Has abstractyes

Explore more

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