Reflections on Developments in Health Promotion in the past Quarter Century from Founding Members of the <i>American Journal of Health Promotion</i> Editorial Board
Bibliographic record
Abstract
In celebration of the 25th anniversary of the founding of the American Journal of Health Promotion, all 14 of the founding members of our editorial board who are still affiliated with the Journal submitted reflections on how the field of health promotion has evolved in the past quarter of a century. Comments from 10 of them are below. Comments by four of them (J. Allan Best, PhD, Ron Goetzel, PhD, Barry Franklin, PhD, and Lawrence Green, DrPH) and comments by me are published as separate articles in this issue. As I look at the photos of these 14 people at the top of this page, I see 14 talented scholars and practitioners, 14 kind souls, 14 friends, and 14 middle-aged (and plus) white men. They are middle-aged (and plus), because they have been with us for 25 years. They are white and male, because that was the nature of our field 25 years ago. I am pleased to say that 148 (52%) of the 285 members of our current editorial team, and three of our four Associate Editors in Chief, are women. I don’t have an accurate racial breakdown of our current editorial team, but I do know that we are much more diverse than we were 25 years ago. These changes in gender and race are also a reflection of changes in the leadership of our field which I believe will help us better understand all populations and ultimately produce programs that will engage more people and produce even better outcomes.
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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 | 0.068 | 0.158 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.032 | 0.015 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.020 | 0.040 |
| Insufficient payload (model declined to judge) | 0.015 | 0.013 |
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".