Bibliographic record
Abstract
There are approximately 390 million people over the age of sixty-five in the world today, and the number is expected to increase to 800 million by the end of the first quarter of the twenty-first century! Here in North America, one out of eight Americans is sixty-five years of age or older. Every day more than 5,500 Americans celebrate their sixty-fifth birthday, and that number is expected to grow rapidly in the years ahead (ERLC, 1). On Larry King Live, former president Bill Clinton recently agreed with health professionals who predict that by 2025 people will live to one hundred years old and beyond. As the percentage of older people increases, care related to the aging— along with its problems, attitudes, and responsibilities— become matters of increasing concern. Faced with these statistics and issues, we must ask ourselves how we can offer better pastoral assistance and care for the aged and the sick of our society. Interestingly, the Bible speaks much about aging (Harris 2008, 11–51). By exploring the biblical perspectives on this topic, we can hope to gain a greater
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".