Title III-E Report YTD 1st Quarter-4th Quarter 2007 \n
Bibliographic record
Abstract
Family Caregiver Support Program (Title III-E) - The Administration on Aging (AoA) has determined that for Title III-E, the actual family caregiver is the client, not the older person receiving the services. Iowa NAPIS (National Aging Program Information System) collects and reports Title III-E service/performance data and related program management information to the federal and state government in a format like the other Title III services. The major shift in reporting relates to who is the client. As a result, this Title III-E Client/Service Unit Report shows the number of caregivers who receive services and the number of units by service category from the Title III-E funding of the Older Americans Act, the AoA, and limited state general fund dollars. Additionally, it shows the number of persons served by individual services and total "unduplicated" client count across all services. In other words, if you add the total number of clients (caregivers) from all services, it is higher than the actual number of persons served across all services because some people need and receive more than one service. (Please note: this is preliminary data, and may be subject to change.) \nTitle III-E Report YTD 1st Quarter 2007 \nTitle III-E Report YTD 2nd Quarter 2007 \nTitle III-E Report YTD 3rd Quarter 2007 \nTitle III-E Report YTD 4th Quarter 2007 \n \n \n
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.477 | 0.528 |
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".