Worth a Thousand Words: Crime Scenes Represented by Photojournalists and Forensic Photographers in Brazil
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
This article compares how crime scenes are represented by photojournalists and forensic photographers in the city of Brasília. It starts from the premise that crime scene photography adheres to the social and professional contexts of the professional group that is taking it who, in turn, determines its identities, practices and conventions. The methodology consists of an analysis of 168 photos taken of three cases of femicide that occurred between 2016 and 2019, and in-depth interviews conducted with three photojournalists and three forensic photographers. News photographs place their importance on the selection of information that is going to be shown to their audience, usually choosing people and elements that evoke emotions. Forensic photographers emphasize documentation and control, using high-angle shots to capture everything. Both fields claim objectivity in their production, but in opposite ways, as forensic photography attempts to prove what is shown, and news photography hides and distorts elements to appeal to its audience. This paper looks at the role photography plays in building social reality, showing the same scene from the same incident and how its representation may differ according to who makes the image, the protocols they follow, and also who these images are taken for.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it