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Record W1964103321 · doi:10.1080/10615806.2015.1036047

The two roads of passionate goal pursuit: links with appraisal, coping, and academic achievement

2015· article· en· W1964103321 on OpenAlexafffund
Benjamin J. I. Schellenberg, Daniel S. Bailis

Bibliographic record

VenueAnxiety Stress & Coping · 2015
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGoal pursuitCoping (psychology)PsychologyGoal orientationApplied psychologyMathematics educationSocial psychologyPsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: In this research, we tested the role of cognitive appraisals in explaining why harmonious and obsessive passion dimensions are related to distinct forms of coping and explored if performance was impacted by these appraisal and coping processes. DESIGN: Undergraduate students (N = 489) participated in a longitudinal study and completed three surveys throughout the course of an academic year. METHODS: Participants completed assessments of both passion dimensions (Time 1), reported how they were appraising and coping with the mid-year examination period (Time 2), and provided consent to obtain their final grade in Introductory Psychology (Time 3). The hypothesized model was tested using structural equation modeling. RESULTS: Harmonious and obsessive passion dimensions were linked with approach and avoidant coping responses, respectively. Cognitive appraisals, particularly appraisals of challenge and uncontrollability, played an indirect role in these relationships. In addition, both appraisals and coping responses had an indirect effect in the relationship between passion dimensions and final grade. CONCLUSIONS: These results identify cognitive appraisal as a reason why passion dimensions are linked with distinct coping tendencies and demonstrate the role of appraisal and coping processes in the journey to passionate goal attainment.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score0.514

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.345
Teacher spread0.308 · 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 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

Citations39
Published2015
Admission routes2
Has abstractyes

Explore more

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