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Record W4242826810 · doi:10.32920/ryerson.14664204

Tour Through Scotland: A Finding Aid of Scottish Travel Photography at the Archival & Special Collections, University of Guelph

2021· preprint· en· W4242826810 on OpenAlexfundaboutno aff
Danielle McAllister

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsnot available
FundersUniversity of Guelph
KeywordsPhotographyTourismGlossaryPublishingIndex (typography)Library scienceSpecial collectionsPeriod (music)Visual artsNarrativeHistoryArchaeologyArtWorld Wide WebComputer scienceLiterature

Abstract

fetched live from OpenAlex

Among the various collections housed in the Archival & Special Collections CASC) at the University of Guelph is a group of photographic material that exhibits the integral role photography played in Scotland's tourism industry from the nineteenth and early twentieth centuries. Photographic publishing firms such as G.W. Wilson & Co. and Valentine & Sons, Ltd. incorporated photography into their commercial repertoires and both helped to create and capitalize on Scotland's vibrant tourism industry during this period. This thesis focuses on this specific group of material that includes four bound albums, five opalines, seven travel view books, and over four hundred stereographs, and additionally looks at how institutions such as the ASC use descriptive tools like finding aids to provide access to and information about their collections. This thesis project reevaluates the structure and role of the finding aid as applied to photographic material in archival collections. Additional components such as a biographical sketches, a glossary of photographic terms, a geographic index, and a historical overview, have been incorporated to further demonstrate how a finding aid can build a greater web of connections and narratives for such collections.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.221

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.002
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0210.002

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 head0.051
GPT teacher head0.232
Teacher spread0.182 · 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.

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 routes2
Has abstractyes

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