Communication and Marketing as Tools to Cultivate the Public’s Health
Bibliographic record
Abstract
Background Communication is rapidly coming to be recognized as a core function, or core competency, in the eld of public health. Several developments over the past few years illustrate this fact. In 2003, the Institute of Medicine identied communication as a core public health competency and called for eorts to enhance the communication skills of the public health workforce.[1] Over the past ve years the National Cancer Institute-the largest biomedical research funding agency in the U.S.—has signicantly increased the size of its health communication research portfolio after identifying health communication as vital to future progress in cancer control.[2] In 2005, the Directors-General of National Public Health Institutes (NPHIs)— technical assistance units established within national health ministries-identi-ed health communication as a core function of NPHIs,[3] and the Pan American Health Organization committed to “better utilize or increase, if needed, the numbers of ... communication experts” working in its member organizations.[4] Between 2004 and 2006, several U.S. schools of public health launched Masters in Public Health (MPH) degree programs in public health communication[5- 7]—which added signicant new training capacity on top of the one extant program[8]—and the U.S. Association of Schools of Public Health published a draft set of communication competencies that are proposed to be required of every Masters in Public Health (MPH) graduate from accredited U.S schools of public health.[9] Although marketing has not been formally recognized as a core public health function or competency-possibly because negative associations toward the concept by some in public health as a result of its roots in the business sector-many leading public health organizations are seeing its relevance to public health purposes and building their capacity in this discipline. Health Canada rst established it Social Marketing Unit in 1981 and continues to expand its social marketing expertise.[10] e U.S. Centers for Disease Control and Prevention established the National Center for Health Marketing in 2004,[11] and a number of U.S. states-Arizona, California, Ohio and North Carolina, at a minimum-have recently established social marketing units. e National Health Service in the UK is currently considering a proposal to integrate social marketing as a core strategy in managing the health of the British population,[12] and public health organizations in the pacic region are working to enhance their marketing capacity.[13] Health communication and social marketing have been vibrant areas of academic research and professional practice for several decades,[14,15] with both areas of inquiry yielding dedicated journals,[16,17] numerous books,[18-21] and myriad peer-reviewed manuscripts published in public health journals.[22-24] What has been slower to emerge, however, is a coherent sense of precisely how these disciplines can inform the practice of public health.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.027 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".