Bibliographic record
Abstract
Deleuze’s approach to neorealism is unusual. Guided by his unorthodox synthesis of Henri Bergson and Andre Bazin, he does not focus on the documentary techniques or the didactic messages of these films but rather on the new kinds of scenarios they explore — ‘situations which we no longer know how to react to, in spaces which we no longer know how to describe’. 1 Neorealism takes these ‘unanswerable situations’ as its basic raw material. Roberto Rossellini’s films are usually associated with the emergence of a new kind of realism that eschews the fantasy space of Hollywood cinema to present life as it really is. It made use of non-professional actors, real locations and no scripts. On this view, it prefigures the French New Wave, cinema verité, various kinds of documentary realism and even newer forms of user-generated media. For Deleuze, however, what matters in neorealism is not any social content, or humanitarian message. Rosselini’s project is not a sociological exercise of providing context to the plight of war orphans and refugees and all the other damaged lives of the post war years. In fact, just the opposite seems to be the case. Neorealism attempts to strip away context and narrative in order to expose the enigmatic quality of a situation, and from there to teach us something about the nature of situations per se. In this way, it realizes the capacity of cinema to teach us something about the most basic properties of kinesis, that is to say, the movement or unfolding of events. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.023 |
| Scholarly communication | 0.016 | 0.019 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.053 | 0.007 |
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".