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On the Development of Harmonious and Obsessive Passion: The Role of Autonomy Support, Activity Specialization, and Identification With the Activity

2009· article· en· W2140969559 on OpenAlexaff
Geneviève A. Mageau, Robert J. Vallerand, Julie Charest, Sarah‐Jeanne Salvy, Nathalie Lacaille, Thérèse Bouffard, Richard Koestner

Bibliographic record

VenueJournal of Personality · 2009
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsMcGill UniversityUniversité du Québec à MontréalUniversité de Montréal
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsPassionAutonomyPsychologySocial psychologyDevelopmental psychologyPolitical science

Abstract

fetched live from OpenAlex

Recent research (Vallerand et al., 2003) has supported the existence of two types of passion for activities: a harmonious and an obsessive passion. The purpose of this investigation was to study the processes likely to lead to the development of passion. Three studies using correlational and short-term longitudinal designs with varied populations ranging from beginners to experts reveal that identification with the activity, activity specialization, parents' activity valuation, and autonomy support predict the development of passion. Furthermore, results show that children and teenagers whose environment supports their autonomy are more likely to develop a harmonious passion than an obsessive one. Conversely, children and teenagers who highly value activity specialization, who rely heavily on their activity for self-definition, and whose parents highly value the activity are more likely to develop an obsessive passion.

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)0.008
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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.291
Teacher spread0.264 · 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

Citations438
Published2009
Admission routes1
Has abstractyes

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