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Record W4253790310 · doi:10.32920/ryerson.14653758.v1

Urban decay: a case study of the negatives in the Toronto Telegram fonds, Clara Thomas Archives and Special Collections

2021· preprint· en· W4253790310 on OpenAlexfundaboutno aff
Jessica Rachel Bakst Gruneir

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicPhotography and Visual Culture
Canadian institutionsnot available
FundersYork University
KeywordsNegativeCellulose acetateSpecial collectionsHistoryLibrary scienceCelluloseArtChemistryComputer scienceVisual artsOrganic chemistry

Abstract

fetched live from OpenAlex

The negatives in the Toronto Telegram fonds (1876-1971), at the Clara Thomas Archives and Special Collections at York University, in Toronto, Canada are representative of eras in history and are of great historical, geographic and intrinsic value. The declining condition of the negatives is of significant concern for the longevity of these photographic artifacts. The fundamental value this fonds has to support research and teaching at the Clara Thomas Archives and Special Collections, York University Library and York University must be recognized. My research concentrates on the 830,000 negatives, which include glass plate, cellulose nitrate, and cellulose acetate materials, all suffering from minor to severe forms of chemical and physical degradation. Vinegar syndrome is a major problem; the consequences of which are permanently deformed cellulose acetate negatives. This case study investigates the deteriorating condition of each type of negative within this fonds, and suggests appropriate measures for decelerating degradation.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score0.580

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0120.006
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.045
GPT teacher head0.285
Teacher spread0.240 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations4
Published2021
Admission routes2
Has abstractyes

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