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Record W2790689068 · doi:10.5334/kula.4

The Oral History of Photographs: Collaboration, Multi-Level Engagement, and Insights from the Adrian Paton Collection

2018· article· en· W2790689068 on OpenAlex
Craig Harkema, Keith Carlson

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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueKULA knowledge creation dissemination and preservation studies · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicOral History, Memory, Narrative Analysis
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDigitizationOral historyFolkloreTransformative learningInstitutionSociologyCultural heritagePublic relationsDigital collectionsLibrary scienceVisual artsMedia studiesHistoryPolitical scienceSocial scienceArchaeologyEngineeringComputer scienceArtPedagogyAnthropologyTelecommunications

Abstract

fetched live from OpenAlex

This paper outlines notable features of the Adrian Paton Photo and Oral History Collection at the Saskatchewan History & Folklore Society (SHFS) and discusses aspects of the relationships formed between the local collector, faculty at the University of Saskatchewan, the SHFS, and members of the community-based cultural heritage digitization project during the collection’s creation and curation. We also outline the benefits and challenges for university-led digital projects that seek to partner with a wide range of participants, with a focus on community members, local organizations, and students enrolled in programs at their institution. Additionally, we discuss the transformative potential of such partnerships for academic institutions and what to consider when entering into collaborations of this nature.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.726
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.144
GPT teacher head0.345
Teacher spread0.202 · 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