Seeing Blackness: Found Footage and the Archive as Modes of Investigation in the Hanging of Marie-Josèphe Angélique
Bibliographic record
Abstract
Marie-Josèphe Angélique was a black slave in New France (Montreal, Canada) tried for setting a fire, burning down much of what is now known as Old Montreal. She was brutally tortured and hanged, her body eventually burned to ash in 1734. Over the last years, there has been an increased national interest in the figure of Marie-Josèphe Angélique, however, scholars and authorities have not come to an agreement about her hanging. Some speculate that the authorities, under pressure from an enraged population seeking a scapegoat, took the easy way out and condemned Angélique. Others believe that Angélique was determined to undermine the slave system and started the fire as revenge against her owner. I decided to explore these racial anxieties through my experimental documentary Anna O and the Case of Displaced Memory (2017), in which I used the hanging of Marie-Josèphe Angélique as an entry point to explore the relationship between the constitution of a racialized self, racial representation and the construction of collective memory, employing found footage as a mode of inquiry and aesthetic exploration into notions of appropriation, documentation and intertextuality. Article received: December 28, 2017; Article accepted: January 10, 2018; Published online: April 15, 2018; Original scholarly paper How to cite this article: Arroyo, Victor. "Seeing Blackness: Found Footage and the Archive as Modes of Investigation in the Hanging of Marie-Josèphe Angélique." AM Journal of Art and Media Studies 15 (2018): 147–158. doi: 10.25038/am.v0i15.238
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.031 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".