Image and text, the creation of JFK as a cultural icon
Bibliographic record
Abstract
My purpose in this thesis is not only to argue that we can use theories about works of art to discuss a human icon but that doing so does perhaps give us some power over the icon. There are many disciplines of study--semiotics, studies in cinema and mass media, comparative studies in the arts--which are all focused on pictorial representation and visual culture. I want to take this approach a step further, and include the humanistic side of pictures. I want to take a human icon, substitute it for a picture, and apply theories about pictures, using image, text, and history. Mitchell's 'Picture Theory' is not a theory about pictures: it is a way of looking at theories--how they are "pictured." My thesis in turn is concerned with the way that we picture a human icon and how it functions as a materialist work of art that represents something other than exactly what one sees. Specifically, I propose to use aspects of Interarts Theory, normally concerned with visual and verbal art, and apply it practically to thehuman icon of John Fitzgerald Kennedy (JFK). (Abstract shortened by UMI.)
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 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".