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Record W22217235 · doi:10.1139/y11-102

(Bort)förklaringar till varför reflexer inte används : Ålder, kön och Construal Level Theory

2013· article· en· W22217235 on OpenAlexvenueno aff
Maria Lyytikäinen

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsTheologyConstrual level theoryPhilosophySocial psychologyPsychology

Abstract

fetched live from OpenAlex

Genom att använda reflex kan gångtrafikanten i mörkret upptäckas 100 meter tidigare av bilisten. Ändå används de inte. CLT rör hur mentala konstruktioner formas och hur individen rör sig mellan psykologiska distanser på abstrakta eller konkreta nivåer. Kognitiv dissonans innebär att beteenden ligger i konflikt vilket leder till obehag som behöver reduceras. En enkätundersökning med 120 deltagare genomfördes med syftet att se om individer inomhus i dagsljus förklarade sin frånvaro av reflexer abstrakt medan individer utomhus i mörker förklarade konkret. Resultatet visade inget stöd för detta men däremot att män hade en tendens att förklara sig mer abstrakt än kvinnor samtidigt som de använde reflexer mer sällan och ansåg dem vara mindre viktiga för säkerheten. Resultatdiskussionen gällde om frågorna i indelningarna av abstrakt och konkret är alltför olika. Dessutom diskuteras om den psykologiska distansen var för liten eller om kön avgör mer för typ av förklaring än miljön.

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 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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.005
Scholarly communication0.0030.005
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0180.006

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 head0.033
GPT teacher head0.322
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2013
Admission routes1
Has abstractyes

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