Congregations and Social Services: An Update from the Third Wave of the National Congregations Study
Bibliographic record
Abstract
Congregations and other religious organizations are an important part of the social welfare system in the United States. This article uses data from the 2012 National Congregations Study to describe key features of congregational involvement in social service programs and projects. Most congregations (83%), containing 92% of religious service attendees, engage in some social or human service activities intended to help people outside of their congregation. These programs are primarily oriented to food, health, clothing, and housing provision, with less involvement in some of the more intense and long-term interventions such as drug abuse recovery, prison programs, or immigrant services. The median congregation involved in social services spent $1500 per year directly on these programs, and 17% had a staff member who worked on them at least a quarter of the time. Fewer than 2% of congregations received any government financial support of their social service programs and projects within the past year; only 5% had applied for such funding. The typical, and probably most important, way in which congregations pursue social service activity is by providing small groups of volunteers to engage in well-defined and bounded tasks on a periodic basis, most often in collaboration with other congregations and community organizations.
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 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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".