Bibliographic record
Abstract
Healthy People 2010 provides our Nation with the wide range of public health opportunities that exist in the first decade of the 21st century. With 467 objectives in 28 focus areas, Healthy People 2010 will be a tremendously valuable asset … . Healthy People 2010 reflects the very best in public health planning—it is comprehensive, it was created by a broad coalition of experts from many sectors, it has been designed to measure progress over time, and, most important, it clearly lays out a series of objectives to bring better health to all people in this country. The current responses to the traditional health perils … have been weakened. At the same time, it seems to this outsider as though the entire public health establishment is united around the proposition that massive public action should be taken to deal with the new “epidemics,” such as obesity and diabetes … . But the use of the term “epidemic” is just the wrong way to think about this issue. There are no noncommunicable epidemics … . Yet the designation [of] obesity as a public health epidemic is designed to signal that state coercion is appropriate … .
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 | 0.033 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.018 | 0.085 |
| Scholarly communication | 0.018 | 0.027 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.028 | 0.033 |
| Insufficient payload (model declined to judge) | 0.008 | 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".