Bibliographic record
Abstract
Abstract A Medium Seen Otherwise examines the innovative incorporation of photography into documentary film, exploring the various ways in which this specific manifestation of intermediality permits us to see both photography and documentary film otherwise. Photographs, whether professional or vernacular, are conventionally understood to furnish documentaries with indexical evidence and visual illustration of history, yet the spatio-temporal dimensions of film permit documentaries to illuminate photography’s wider capacities beyond the merely representational. Through an investigation of how political, historical, and art documentaries engage with photographic images, objects, and archives, the book argues that film allows us to better understand what people do with analog and digital photographs as material objects that enable particular forms of social and political relationality through multisensory experience. Moreover, film can bring the event of photography into fuller view, demonstrating how no single participant in it (photographer, subject, camera, photograph, or viewer) has sovereignty over its affect, meaning, or value. Combining new critical perspectives on well-known documentary filmmakers and photographers (Agnès Varda, Rithy Panh, Edward Burtynsky, Malick Sidibé, Vivian Maier, JR, Ken Burns, Errol Morris, and Akram Zaatari) with analysis of lesser known, but important, documentaries, the book investigates a global range of documentary and vernacular photographic contexts, including Lebanon, Palestine, Mali, Congo, Cambodia, Ireland, Spain, Mexico, Chile, Canada, and the United States. While authorship and representation remain common rhetorical frameworks for documentaries about photography, A Medium Seen Otherwise offers an account of how the intermediality between documentary film and photography can posit far more expansive conceptions of both media.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.046 | 0.003 |
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".