Feeding the Flock: The Role of the Revenue Portfolio in the Financial Growth of Congregations and Religious Organizations
Bibliographic record
Abstract
ABSTRACT There have been fewer population‐level studies of religious organization revenues compared to other nonprofit organizations. This discrepancy is due to the exemption of houses of worship from filing the U.S. Form 990, which is the basis for most nonprofit financial analysis in academic literature. Using granular financial data on over 30,000 religious organizations in Canada from 2009 to 2016, we explore the characteristics of the revenue portfolios for this under‐studied subsector of tax‐exempt organizations. In addition to providing useful descriptive information, such as the differences between funding portfolios by religion or denomination, we identify characteristics associated with financial growth using dynamic difference‐generalized method of moments estimations. We find that donations where receipts were given drive almost all portfolios, while revenues that comprise the portfolio fringe vary widely in form and importance for growth. This study yields information useful to practitioners and researchers interested in nonprofit finance and the financial management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".