Fotonovela as a Research Tool in Image-Based Participatory Research with Immigrant Children
Bibliographic record
Abstract
In this article the authors explore the effect of word-image relationships on the collection of data and the reporting of research results for a study involving the development of a series of fotonovelas with immigrant children in an inner-city school. The central question explored in this article is Can experiences such as producing visual narratives in the form of fotonovelas stimulate multiple expressions of voice and position and bring awareness of embodied ways of communicating in a culture-rich school context? The processes involved in collaboratively developing the photographic narrative format of the fotonovela combine visual elements and structures and embodied, reflective performance together with written text. As a research method fotonovela does not merely translate verbal into visual representations but constructs a hybrid photo-image-text that opens new spaces for dialogue, resistance, and representation of a new way of knowing that changes the way of seeing and has the potential to change the author's and the reader's self-understanding.
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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 | 0.061 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".