Rationalizing Consumption: Lejaren à Hiller and the Origins of American Advertising Photography, 1913–1924
Bibliographic record
Abstract
B y the second decade of the twentieth century, the rationalization of the American economy threatened to founder, not on the shoals of production or distribution, where mechanization and national transportation systems had nearly vanquished challenges to middle-class material abundance, but on those of consumption. As numerous historians have argued, advertising matured as a profession in response to a new problem for American business: how to stimulate demand among white, middle-class consumers for the machined cornucopia of standardized products filling the shelves of American retail establishments. Whereas earlier advocates of American productive efficiency, such as the motion-study experts Frank and Lillian Gilbreth, had championed the use of photography in rationalizing the working body in production, by the 1920s the influence of applied psychology had reoriented managers toward an appreciation of the mind as the critical element of rationalized consumption. 2 Achieving greater sales in an increasingly competitive and national marketplace required convincing hesitant consumers that individual difference and personal meaning could be theirs, despite a regularized landscape of standardized goods. Corporations increasingly hired advertising agencies and their creative staffs, in Jackson Lears’ phrase, to “surround mass-produced goods with an aura of uniqueness” designed to stimulate consumption through the promise of individuality. 3 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.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".