Multidisciplinarity in health promotion: a bibliometric analysis of current research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Health promotion (HP) is a relatively recent field that stems from, notably, public health, sociology, political science, psychology and education. This multidisciplinarity has contributed to HP's challenged institutionalization. Scholars have so far predominately explored HP's multidisciplinarity using anecdotal approaches, limiting our understanding of the breadth and interplay of the disciplines constituting HP research. The overall aim of this paper is to contribute to a better understanding of HP's multidisciplinarity using a bibliometric approach. We developed a three-pronged approach: (i) we examined the most cited journals within Health Promotion International; (ii) we asked an international panel of HP scholars (n = 27) to vote on the journals most relevant to their work; (iii) we examined the most common words in article abstracts among journals which received the highest number of votes. We used multiple correspondence analyses to examine similarities between HPI references, scholars' votes and abstracts' words. We found evidence that HP research reached across numerous disciplines but segregated into distinct subgroups with conflicting perspectives. We found that HPI was the only journal that was identified as relevant by a majority (81% of participants). Multidisciplinarity is a key feature of HP. It can strengthen HP by enriching our understanding of health and social issues from a variety of perspectives, but it may also divide experts into disciplinary silos. This may ultimately weaken its institutional pathways and its contribution to public health. More academic venues and institutions should be developed to facilitate collaboration among HP scholars and practitioners.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.088 | 0.076 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it