History Moves: Mobilizing Public Histories in Post-Digital Space
Bibliographic record
Abstract
Similar to most cultural forms today, history is collected, edited, manipulated, stored, displayed, distributed, and otherwise produced through a complex network of post-digital techniques and media. It is often produced only by historians. History Moves is a public history project that aims to produce cogent and collective historical experiences within the cultural frame of mutable and highly distributed media forms. It does this by bringing history, design, and historical subjects into conversation to shape public space. The project uses a participatory process that mobilizes people to interpret history by mobilizing digital and analogue media. History Moves transforms historical subjects into history-makers while simultaneously and repeatedly transfiguring media into forms that are engaging and accessible to widely distributed audiences. This article recounts a case study where History Moves worked with a group of women living with HIV/AIDS to present a history of the epidemic and a women’s history of Chicago. We suggest that the example provides a model for how to build participatory digital history projects and collaborative history displays.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.021 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.002 | 0.025 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".