The “Universal Language of Images”: Interdisciplinary Assemblages in Postwar Experimental Cinema.
Bibliographic record
Abstract
This dissertation offers a contextualisation and critical engagement with artistic practices that developed during the postwar period in North America (1948-1980), when the universalist discourse of the planet as a “global village” gained popularity across the Western world. As a cultural history of universalism and its fissures, this project places experimental cinema and visual culture exhibition within a network of interdisciplinary and multimedia investigations in communications, information technology, sociology, and anthropology. Filmmakers and curators drew from these networks to develop a unique visual grammar that embraced the principle of assemblage, bringing together disparate objects and data to produce new cultural meanings arising from their juxtaposition. This research situates experimental cinema within a larger universalist cultural movement. It provides a critical reading of a selection of curatorial and artistic practices concerned with the formulation of what Stan VanDerBeek termed “a universal language of images” through the analysis of three case studies: Harry Smith’s collection of objects, VanDerBeek’s Movie-Drome, and the Indians of Canada Pavilion at Expo 67. \nThe chapters shed light on three modalities of the collection and display of data as means to formulate a global language of images: 1) the anthropological impulse to document the recurrence of visual symbols across the world through ethnographic collecting, 2) the focus on technologies of communications as receivers, collectors, and transmitters of information, and 3) the juxtaposition of photographs and artworks in exhibition scenography to formulate a global indigeneity. Despite the humanist impulse to connect people across cultures, the ethnographic and gendered “Other” often remains trapped and overlooked in archives and collections. Historical contextualisation and close archival research open these archives to multiple perspectives and interpretations, to show how their collections are the result of cultural encounters and unequal exchanges. These archives reveal that, paradoxically, forms of postcolonial discourses were born from the totalising impulse of universal projects. Identifying a universalist visual culture and its ideological limits paints a nuanced and inclusive history of the postwar period that accounts for its frictions and ambivalences.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.046 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".