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Record W2947688515 · doi:10.1177/0305735619844589

Persisting with a music career despite the insecurity: When social and motivational resources really matter

2019· article· en· W2947688515 on OpenAlexaff
Stacey L. Parker, Catherine E. Amiot

Bibliographic record

VenuePsychology of Music · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPsychologyConservation of resources theorySocial psychologyEmotional exhaustionCareer developmentBurnoutClinical psychology

Abstract

fetched live from OpenAlex

Drawing on conservation of resources theory and self-determination theory, coworker support and work motivation were investigated as resources that should buffer or mitigate the negative consequences of career insecurity for professional musicians. We surveyed 200 professional musicians. Analyses revealed that only those musicians with low career insecurity and better-quality motivation (i.e., either high autonomous or low controlled) were less prone to problem drinking. Importantly, the combination of high coworker support and high autonomous motivation was associated with less emotional exhaustion from career insecurity. These resources were not simply stress-buffers of career insecurity, but helped well-resourced musicians thrive on career insecurity. Additionally, it was found that career insecurity was associated with greater intentions to leave the profession for all musicians, except for those with high controlled motivation when they also had access to high coworker support. For these musicians, having access to supportive coworkers was important for persisting with their music career despite the insecurity.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.998

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.237
Teacher spread0.207 · 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.

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

Citations34
Published2019
Admission routes1
Has abstractyes

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