The Social Capital Effect In Nonprofit Human Service Organizations: An Examination Of Potential Outcomes Of Organizational Social Capital Related To Effectiveness
Bibliographic record
Abstract
The study provided for a more complete understanding of social capital theory and its applicability to nonprofit human service organizations (NPHSOs). The initial analysis included an examination of potential outcomes of social capital (e.g., human capital, financial capital, volunteerism, and program effectiveness); and secondly, the study examined possible mediating effects between social capital and program effectiveness in NPHSOs, while controlling for demographic differences. Primary data was collected through a self-administered questionnaire distributed to a sample of NPHSOs, United Way partner agencies in the eight most populated regions in the State of Texas. The survey response rate, after attrition resulted in 42.7% with a sample size of N = 163 NPHSOs. A four-step approach to modeling was selected to examine the data, which required the use of two statistical softwares: SPSS version 15 and Amos version 7. The main statistical technique utilized for hypotheses testing was Structural Equation Modeling (SEM). The SEM approach involved an exploratory rather than confirmatory approach to model specification. An integrated SEM was proposed which incorporated the potential outcomes of social capital as mediating the relationship between social capital and program effectiveness, while controlling for demographic differences. The factor-analytic model, utilizing both a CFA and EFA approach provided valuable insight for model modification to achieve a better data-to-model fit, and helped to determine the most relevant indicators for the study constructs to test the structural model. The model respecification resulted in a final SEM reflective of the results from the EFA and CFA, and was validated by various goodness-of-fit indices. The hypotheses testing resulted in four direct relationships which were statistically supported. Three direct relationships were interpreted as outcomes of social capital, with increased social capital being positively related to total revenue, volunteerism, and program effectiveness. A significant path was also detected from total revenue to human capital in the hypothesized direction. The control variables (age of the organization, size of the organization, and size of region) were positively correlated to total revenue, and size of the organization was positively related to social capital. No mediating effects were supported by the sample data.
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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".