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Record W3134981643 · doi:10.21203/rs.3.rs-240866/v1

A Common Human Problem Has a Name: Misokinesia

2021· preprint· en· W3134981643 on OpenAlexaff
Sumeet M. Jaswal, Andreas D. Blesser, Todd C. Handy

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPhenomenonPopulationPsychologyHatredCognitive psychologySocial psychologyDevelopmental psychologyDemographySociologyEpistemology

Abstract

fetched live from OpenAlex

Abstract Misokinesia –– or the ‘hatred of movements’ –– is a psychological phenomenon that is defined as a strong negative affective or emotional response to the sight of someone else’s small and repetitive movements, such as seeing someone mindlessly fidgeting with a hand or foot. Among those who regularly experience misokinesia, there is a growing recognition of the challenges that it presents, as evidenced by blossoming on-line support groups. Yet surprisingly, scientific research on the topic is lacking. This article is novel in systematically examining whether misokinesia exists in the non-clinical population and if there are observable individual variability in the intensity or extent of reported misokinesia sensitivity in the general population. Across three studies that included 4100 participants, we confirmed the existence of misokinesia as a phenomenon in a non-clinical population, with approximately one-third of our participants self-reporting some degree of misokinesia sensitivity to the repetitive, fidgeting behaviors of others as encountered in their daily lives. Moreover, variability in the range of misokinesia sensitivities showed that the negative social-affective impacts that one experiences may grow with age. This study shows that a large population of the public may be suffering from something that has received little formal recognition.

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)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.008
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.464
GPT teacher head0.523
Teacher spread0.059 · 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 designTheoretical or conceptual
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

Citations1
Published2021
Admission routes1
Has abstractyes

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