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Record W3043551697 · doi:10.7939/dvn/waj9ug

Local Music Collections and Collecting in Canada

2018· dataset· en· W3043551697 on OpenAlex
Carolyn Doi

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

VenueUniversity Library (University of Saskatchewan) · 2018
Typedataset
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsUniversity of AlbertaUniversity of Saskatchewan
Fundersnot available
KeywordsGeographyVisual artsArchaeologyArt

Abstract

fetched live from OpenAlex

This dataset results from an online survey of Canadian libraries who have local music collections. The survey was conducted from May 3, 2018 to May 22, 2018. The purpose and objectives of the survey were to understand the state of local music collections across Canada. Specifically, to 1) identify where collections of local music are held, what music(s) they document, and what evidentiary value they possess; and 2) to understand the perceived value of collecting local music, and record local music collection management practices currently used by public institutions to determine areas where practices may be improved. A targeted sample of Canadian libraries thought to potentially contain local music collections were recruited via email distribution. The data are de-identified responses to the survey.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.339
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.000

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 head0.028
GPT teacher head0.153
Teacher spread0.125 · 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