MétaCan
Menu
Back to cohort
Record W4239591052 · doi:10.32920/ryerson.14649735

Stereo pictures in this mount were not taken by view-master: an illustrated description of the view-master personal stereo system

2021· preprint· en· W4239591052 on OpenAlexaff
Jamie Powell Sheppard

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicPhotography and Visual Culture
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAmateurStereoscopyPhotographyVisual artsComputer scienceComputer graphics (images)ArtComputer visionHistoryArchaeology

Abstract

fetched live from OpenAlex

The View-Master is a beloved toy, well-known to many. However, most people are unaware of the View-Master Personal Stereo system for creating one’s own View-Master Personal Reels – an unusual combination of vernacular imagery and three-dimensional photography. Unfortunately, little has been written about this system, and the institutional collections of Personal Reels are limited. This thesis describes the View-Master Personal Stereo system and establishes its place in the combined history of both amateur and stereoscopic photography. It reviews the history of View-Master and amateur stereoscopic systems, examines the View-Master cameras and accessories, follows the decline of mid-century amateur stereoscopic photography, and discusses users and collectors of the system. The result is a compilation of information that both defines the View-Master Personal Stereo system and constitutes an argument that the View-Master Personal Reels have a place in institutional collections of vernacular photography.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.039
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0390.008

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.

Opus teacher head0.088
GPT teacher head0.254
Teacher spread0.166 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicPhotography and Visual CultureFrench-language works237,207