Case Studies Of Two Contemporary Faith-Based Organizations That Care For Individuals With Mental Disabilities
Bibliographic record
Abstract
The research uses the case study method. I selected two contemporary faith-based organizations for the case studies. The first agency studied was in the Great Lakes states. It has been ministering to the field of Mental Retardation/Developmental Disabilities for 100 years. The second has ministered in Canada since the 1960s. I selected these two agencies because of their faith-based origins and investigated each through a questionnaire, interviews, on-site visits, and relevant archival data to determine the validity ofmy hypotheses. The research question for this study is, "Do these case studies offer an adequate model for the care of individuals with mental disabilities?" The conclusion of this research is that it validates the hypotheses. Shepherds Ministries has advanced in appropriate independence, meaning graduated responsibility with full accountability, consistent with the Word of God. It continues to advance towards a full agency of services that can be portable to people with mental disabilities. Shepherds Ministries has advanced its behavioral management program for clients. In addition, the issues of ratios of clients to staff continues to be addressed. Shepherds Ministries still maintains its uniqueness in hiring practices and board member requirements. Both education degrees and experience have been upgraded for staff and board members. Shepherds Ministries continues to expand its excellent vocational services. Recommendations for future research are also included in the study.
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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".