“This Prodigious Frightful Fall”: An Exploration of Tourist Images of Niagara Falls in Stereography and on Instagram
Bibliographic record
Abstract
This thesis explores the development of tourist photography through stereography and Instagram utilizing Niagara Falls stereographs from three collections ranging in date from 1850-1905 and Instagram images geotagged to Prospect Point, Niagara Falls, New York, all posted in the same twenty-four hours from August 6-7, 2016. First, a literature survey explores the history of photography at Niagara Falls, the circulation of tourist imagery, and social media and the networked image. It then moves on to an early history of photography at Niagara Falls with an emphasis on stereographs. It continues into a brief history of social media and an explanation of the inner workings of Instagram. Finally, it concludes with comparisons of aesthetic choices, access, and circulation in stereographs and Instagram, all using the case study images. This thesis argues that Instagram follows the same photographic tradition as stereographs and serves many of the same purposes in tourist photography
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".