MétaCan
Menu
Back to cohort
Record W2756378246 · doi:10.3389/fpsyg.2017.01649

Accepting Lower Salaries for Meaningful Work

2017· article· en· W2756378246 on OpenAlexaff
Jing Hu, Jacob B. Hirsh

Bibliographic record

VenueFrontiers in Psychology · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSalaryPsychologySocial psychologySet (abstract data type)Job satisfactionPerceptionMeaning (existential)Work (physics)Scale (ratio)Compensation (psychology)Job attitudeSample (material)Job performance

Abstract

fetched live from OpenAlex

A growing literature indicates that people are increasingly motivated to experience a sense of meaning in their work lives. Little is known, however, about how perceptions of work meaningfulness influence job choice decisions. Although much of the research on job choice has focused on the importance of financial compensation, the subjective meanings attached to a job should also play a role. The current set of studies explored the hypothesis that people are willing to accept lower salaries for more meaningful work. In Study 1, participants reported lower minimum acceptable salaries when comparing jobs that they considered to be personally meaningful with those that they considered to be meaningless. In Study 2, an experimental enhancement of a job's apparent meaningfulness lowered the minimum acceptable salary that participants required for the position. In two large-scale cross-national samples of full-time employees in 2005 and 2015, Study 3 found that participants who experienced more meaningful work lives were more likely to turn down higher-paying job offers elsewhere. The strength of this effect also increased significantly over this time period. Study 4 replicated these findings in an online sample, such that participants who reported having more meaningful work were less willing to leave their current jobs and organizations for higher paying opportunities. These patterns of results remained significant when controlling for demographic factors and differences in job characteristics.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.456

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.303
Teacher spread0.277 · 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

Citations101
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in PsychologySame topicJob Satisfaction and Organizational BehaviorFrench-language works237,207