Writing with light: An iconographic-iconologic approach to refugee photography
Bibliographic record
Abstract
Refugee photography is often used to convey situations of precariousness and urgency, as visibility can help raise awareness and elicit empathy. Critical perspectives in relation to photographic representations can provide more nuanced understandings of refugee lived experiences over time. This article uses the iconographic-iconologic image framework as a process to understand how refugee lived experiences were represented in four photographs from a refugee library collection. These photographs depict different refugee situations from some 20 to 35 years ago. As a refugee studies scholar interested in visual-based research, I wished to analyze how refugee lived experiences were represented through these photographs from another era. The application of the iconographic-iconologic image framework suggests various themes evoked through these photographs, which still have currency in today's highly polemic discourses on the global refugee regime and are still prominent in present-day discourses and contemporary refugee literature. This qualitative analysis shows the potential of photographs to highlight how precarious refugee situations persist over time despite intense international efforts in this field. (author's abstract)
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.010 | 0.023 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".