BRIDGING THE GAP BETWEEN HOSPITALIZATION OF THE HOMELESS, SELF- CARE AND HOUSING: A PROPOSAL
Bibliographic record
Abstract
The purpose of this thesis is to propose the use of a program planning model that will address the lack of respite care, or in other words, the lack of a specific place for recuperation after an illness or injury available for homeless people in Allegheny County. This proposal will incorporate a program planning design of a potential respite program in Allegheny County. This respite care intervention is designed to be part of a county wide effort to eliminate homelessness in Allegheny County led by the Allegheny County Homeless Alliance. This proposal will incorporate the Mobilizing for Action through Planning and Partnerships (MAPP) program model for the intervention design. This is a six-phase process that emphasizes community collaboration and assessment as the driving forces for the creation of an intervention. The six phases of the MAPP model are 1) Organizing for Success/Partnership Development; 2) Visioning; 3) The Four MAPP Assessments; 4) Identify Strategic Issues; 5) Formulate Goals and Strategies; 6) The Action Cycle. This proposal will describe how the Allegheny County Homeless Alliance can conduct the phases of the MAPP model using information previously collected as well as ways they can obtain additional information. The proposal will describe a respite care intervention that is an example of a possible respite care program in Allegheny County. The goals of the program are to improve the health of the homeless as well as to create social support for this population and an opportunity to transition into permanent housing. The public health significance of this proposal is that it will create an intervention for the homeless population of Allegheny County that will allow them to achieve better health status through respite and follow-up care, greater social support and, most importantly, the opportunity to obtain permanent housing in a more direct way than what is the norm.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".