MétaCan
Menu
Back to cohort
Record W2100396492 · doi:10.1002/nml.46

Staffing, retention, and government funding: A case study

2004· article· en· W2100396492 on OpenAlexaffabout
Kunle Akingbola

Bibliographic record

VenueNonprofit Management and Leadership · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsStaffingAgency (philosophy)Government (linguistics)BusinessPublic relationsRetention ManagementMarketingManagementEconomicsPolitical scienceSociology

Abstract

fetched live from OpenAlex

Abstract This study analyzes the implications of government‐contract funding on the staffing pattern of a nonprofit agency, the Canadian Red Cross, Toronto Region. Furthermore, the study explains the implications of the staffing pattern on services and on the agency's organization. Staffing is one area that the literature on nonprofit organizations has not adequately addressed. The findings indicate that contract‐based funding leads to the hiring of temporary staff and affects the retention of employees. Although contract funding has some benefits, temporary staffing is detrimental to the agency's services. It affects not only employee recruitment and retention but also training. The results highlight how change in government funding from grants to contracts resulted in the agency's new staffing strategy and ultimately reduced the effectiveness of the services the agency provided to the community.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.180
GPT teacher head0.319
Teacher spread0.138 · 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 designQualitative
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

Citations47
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueNonprofit Management and LeadershipSame topicNonprofit Sector and VolunteeringFrench-language works237,207