MétaCan
Menu
Back to cohort
Record W2082946399 · doi:10.3389/fnhum.2013.00556

A biological security motivation system for potential threats: are there implications for policy-making?

2013· article· en· W2082946399 on OpenAlexafffund
Erik Z. Woody, Henry Szechtman

Bibliographic record

VenueFrontiers in Human Neuroscience · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsMcMaster UniversityUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsState (computer science)Computer securitySecurity policyComputer scienceRisk analysis (engineering)Internet privacyPsychologyBusiness

Abstract

fetched live from OpenAlex

Research indicates that there is a specially adapted, hard-wired brain circuit, the security motivation system, which evolved to manage potential threats, such as the possibility of contamination or predation. The existence of this system may have important implications for policy-making related to security. The system is sensitive to partial, uncertain cues of potential danger, detection of which activates a persistent, potent motivational state of wariness or anxiety. This state motivates behaviors to probe the potential danger, such as checking, and to correct for it, such as washing. Engagement in these behaviors serves as the terminating feedback for the activation of the system. Because security motivation theory makes predictions about what kinds of stimuli activate security motivation and what conditions terminate it, the theory may have applications both in understanding how policy-makers can best influence others, such as the public, and also in understanding the behavior of policy-makers themselves.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.643

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.157
GPT teacher head0.386
Teacher spread0.230 · 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

Citations31
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in Human NeuroscienceSame topicNeural and Behavioral Psychology StudiesFrench-language works237,207