The Use of Photo-Essay to Report Advances in Applied Science and Health
Bibliographic record
Abstract
Background: In the applied health and science disciples there is an expectation that project work is reported through a publication. The conventional papers written to do this follow a structure that includes sections providing background, methods, results and a discussion or conclusion, supported by figures and tables. Sometimes photographs are included, and with more on-line publications the opportunities have increased for these to be available in full color. Borrowing from the field of photojournalism photo-essays are now a publication option where a series of images are used to tell the story; these are often related to health and well-being.Aims: To summarize the methodology used to effectively combine a series of images with a brief text, and short reference list to create a visually engaging and informative short report.Guidelines: Images are taken throughout the project with consent obtained from those whose images will be recognisable. Creative licence is used to compile representative images into a sequence that conveys the background, method, results and outcome(s) of the project. Images need to be of high resolution; editing for light, colour and contrast, and cropping is allowed to increase their clarity and relevance. The ethics of photojournalism apply making inappropriate manipulation of images or erroneous captions unacceptable.Conclusions: Photo-essays are a novel and informative way to report on an applied health, social or scientific topic. The format is an excellent one to use for a brief report, or to prepare a research presentation for a scientific meeting.Keywords: Photograph, Photojournalism, Photo-manipulation.
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 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 | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".