Tenacious Resins and Residues: Oil Propaganda in Architectural Digest During the Energy Crises of the 1970s
Bibliographic record
Abstract
Architectural Digest was first published in 1920 by John C. Brasfield, a California-based publisher. In 1933, the magazine was purchased by Condé Nast and has since become a popular design magazine, particularly in North America, known for its visually vibrant and abundant advertisements. Car advertisements are among the most recurring ads featured in the magazine. Through an archival investigation of Architectural Digest magazines from 1973 to 1983, I investigate how, if at all, car advertisements in the magazine reflected the 1973 and 1979 oil crises. The 1979 global energy crisis was a period of high energy prices and supply shortages that occurred in the wake of the Iranian Revolution and lasted until about 1983. The crisis was triggered by a number of factors that went all the way back to October of 1973 and the Arab-Israeli war which itself triggered the energy crisis of that year, lasting until at least 1976. I situate this study in Saskatchewan and Alberta, which is where the magazines I investigate physically originated. Thinking with and through these magazines, I read them and their car advertisements to unlearn the way in which they maintain false good life fantasies, and socially and environmentally unjust narratives.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.013 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".