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Record W4246141780 · doi:10.31234/osf.io/vpwbd

Highly Sensitive Adolescents: The Relationship Between Weekly Life Events and Weekly Socioemotional Well-Being

2021· preprint· en· W4246141780 on OpenAlexfundno aff
Shuhei Iimura

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsnot available
FundersLady Davis Institute for Medical ResearchJapan Society for the Promotion of ScienceJewish General HospitalUniversity of Tokyo
KeywordsSocioemotional selectivity theoryPsychologyDevelopmental psychologyVulnerability (computing)Context (archaeology)Perspective (graphical)Maternal sensitivityGeography

Abstract

fetched live from OpenAlex

Recent research into Person x Environment interaction has supported the view that sensitivity to environmental influences is a susceptibility factor rather than a vulnerability factor. Given this perspective, this study examined the role of the adolescent’s sensory-processing sensitivity in the context of weekly life events and weekly socioemotional well-being. In the study, 114 adolescents repeatedly self-reported their sensitivity, recent life events, and recent socioemotional well-being in four surveys at one-week intervals. The results suggested the shape of Sensitivity x Life Events interaction significantly varied from week to week, which is consistent with the vantage sensitivity and diathesis-stress framework. In specific weeks, adolescents with high sensitivity are more likely to benefit from positive events than those with low sensitivity. These sensitive adolescents can be described as developmentally susceptibility rather than vulnerability.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.298
Teacher spread0.260 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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