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Record W4231171888 · doi:10.32920/ryerson.14645898.v1

Finding Wolff: Intellectually Arranging the Werner Wolff Fonds at the Ryerson Image Centre

2021· preprint· en· W4231171888 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsLibrary scienceComputer scienceArt historyArt

Abstract

fetched live from OpenAlex

<p> This thesis presents the results of an applied project in Collections Management, comprising the intellectual arrangement of the Werner Wolff <em>fonds</em> at the Ryerson Image Centre (RIC), and the creation of a finding aid to promote public research in the collection. Wolff was a photojournalist from the late 1930s to the 1980s who amassed a collection of over 1,300 files of photographs and related materials, which his son donated to the RIC in 2009. The project revolved around the organization of the collection inventory, a necessary step before it was possible to proceed with the intellectual arrangement of the <em>fonds</em> into series and sub-series with descriptions of each as set by the Canadian standard Rules for Archival Description. This thesis describes the arrangement of the <em>fonds</em> and the decisions made along the way. It also includes a copy of the finding aid written to promote public access to the <em>fonds</em>. The conclusion outlines the future needs of the collection to finalize the processing of the <em>fonds</em>.</p>

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0720.001

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 head0.035
GPT teacher head0.255
Teacher spread0.221 · 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

Quick stats

Citations14
Published2021
Admission routes2
Has abstractyes

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Same topicArchaeological Research and ProtectionFrench-language works237,207