Images of success: Cosmopolitan Magazine and the mass marketing of non-fiction, fiction, and poetry through illustrations, 1898-1903
Bibliographic record
Abstract
The purpose of this study is to examine Cosmopolitan Magazine’s use of illustrations at the turn of the 20th century in order to affect the interpretative experiences of their readers. Previous scholarship has focused on price, distribution and content development of the magazine during this period, but this thesis aims to show how the visual accompaniments in the non-fiction, fiction and poetry helped Cosmo appeal to a larger audience. The first chapter inspects Cosmo’s genre with the largest number of titles, non-fiction. With the introduction of halftone printing technology, Cosmo and other magazines were regularly able to publish photographs in grayscale for their readers. The introduction of photographs enhanced the educational capacities of the magazine, thereby allowing it to attract wider classes of readers. The second chapter shows how Cosmo transferred this illustration strategy to fiction. Editors facilitated, enhanced, and reinforced readers’ experiences of fiction through the placement of images before, beside, or after corresponding passages of text. The interplay between illustrations and text created a more vivid reading experience for Cosmo’s expanding pubic.The third chapter pushes against the conception of James Landers, who argues that the poetry in Cosmo was generally used for filling space after articles and stories. There is some truth to Landers’s claim, but he fails to see that poetry was increasingly illustrated at the turn of the 20th century. This finding demonstrates that, even in this third genre, Cosmo was applying an editorial strategy involving images in order to reach a larger audience, drawing in readers who might be new to the genre and need visual identifiers.
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 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 | 0.001 | 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 | 0.001 | 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) | 0.000 | 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".