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Record W653464979 · doi:10.1177/0734371x15587980

Money Talks or Millennials Walk

2015· article· en· W653464979 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReview of Public Personnel Administration · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsDalhousie University
Fundersnot available
KeywordsNonprofit sectorWorkforcePrivate sectorPublic sectorBusinessCompetition (biology)Public relationsValue (mathematics)Work (physics)PerceptionMarketingLabour economicsEconomicsEconomic growthPolitical sciencePsychology

Abstract

fetched live from OpenAlex

The nonprofit sector has become increasingly reliant on paid professional staff and now faces competition from the private and public sectors, which often pay higher to attract and retain workers. Although Millennials are attracted to nonprofit work, there are concerns that they will not remain committed to the nonprofit workforce due to low pay. We analyzed data from the 2011 Young Nonprofit Professionals Network Survey to examine the relationship between pay, perceptions of equitable pay, and sector-switching intentions among Millennial nonprofit workers. Although two thirds of the respondents indicate sector-switching intentions, we found no evidence that Millennial nonprofit workers, who are purported to value extrinsic and materialistic rewards, expressed sector-switching intentions on account of pay. However, pay influences the sector-switching intentions of Millennial nonprofit managers and those with advanced education. Our results suggest that the nonprofit sector may be facing challenges in attracting and retaining Millennial managers because of low pay.

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.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.785
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
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)0.0010.000

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 head0.171
GPT teacher head0.395
Teacher spread0.224 · 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