Surrealist histories of language, image, media: Donald Barthelme’s ‘collage stories’
Bibliographic record
Abstract
Abstract Using previously neglected archival materials from the Donald Barthelme Literary Papers at the University of Houston Libraries, my article identifies the sources of Donald Barthelme’s collages and their allusive meanings. In doing so, the author’s under-appreciated relationship with artistic collage techniques is further elucidated, revealing how indebted his work is to the innovations of surrealist collage production. Principal amongst these influences is Max Ernst’s ‘historical’ collage aesthetic. Using the theories of Marshall McLuhan, I argue that Barthelme’s technique of pictorial collage is an attempt to rival contemporary systems of representation (like television and radio), while recognizing the significance of mass media on his work. Capturing the evolving landscape of contemporary mass culture, I examine the relationship between text and image in Barthelme’s short stories.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".