Snapshots with an edge a study of the deckle edge in the North American snapshot
Bibliographic record
Abstract
This thesis takes an object-based approach to the amateur snapshot through an in-depth examination of the deckle edge, a form of snapshot presentation popular in the mid-twentieth century. Research draws primarily from a sample of 321 dated deckle edge snapshots in the collection of the Archive of Modern Conflict, Toronto, and from Kodak trade periodicals held by Ryerson University Special Collections. The thesis examines the formerly undelineated dates of the deckle edge snapshot’s popularity, the various devices used to create the deckle edge, the multiplicities of edge variation blanketed under the term “deckle edge,” the appearance of the deckle edge in Kodak advertising, and the routes by which the deckle edge came to the snapshot. By situating the deckle edge snapshot in these contexts, the thesis demonstrates the value of approaching snapshots as dynamic, physical objects, and the kinds of information that can be derived from their non-image areas.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".