On The Road to Virtue : Meyer Brownstone and the Documentation of Human Development
Bibliographic record
Abstract
On The Road To Virtue is a research project consisting of a thirty-minute documentary film and this supporting thesis paper. The entire project is built on the archival documentation of Meyer Brownstone from his visits to the Salvadoran refugee camps in Honduras in the 1980s. Through a cinematic examination of the visual and audio evidence, as well as Brownstone's commenting on it, we consider his memory of interacting with the refugees and contemplate their own efforts to retain agency in their lives. The film uses three primary vehicles — archival documentation, personal interviews, and enactments —to create a storytelling structure which encourages reflection on the direct testimony of the Salvadoran refugees and on Brownstone’s images, while assessing his evidentiary accounting of life in the refugee camps. The supporting paper and the film both reflect on his commitment to promoting human development in the camps and elsewhere, through the establishment of participatory democracy structures, the maintenance of sustainable living practices, and the insistence on free speech and movement. The film also conveys the fluid relationship between historical events and their contemporary remembrance while this thesis paper critically reflects on the implications of these ideas and the related artistic approaches used to present them in the film.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".