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Record W4254338184 · doi:10.32920/ryerson.14646861.v1

Pilgrimage to solitude : landscapes of Glenn Gould

2021· preprint· en· W4254338184 on OpenAlexaffabout
Mark Laurie

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsToronto Metropolitan UniversityMcGill University
Fundersnot available
KeywordsPilgrimageSolitudeStyle (visual arts)BiographyAntecedent (behavioral psychology)ArtArt historyLiteratureHistoryVisual artsPsychologyArchaeology

Abstract

fetched live from OpenAlex

Pilgrimage to Solitude is a documentary film that explores the geographical places of significance from the life of the late Canadian pianist, composer, and writer, Glenn Gould. In Pilgrimage, the camera documents a number of the physical spaces that feature prominently in Gould's biography, while the soundtrack deploys a sonic technique pioneered by Gould himself in his influential series of sound documentaries: the formal treatment of layered voices which he called "contrapuntal radio." This MFA project paper contextualizes the film within the broader Gould discourse; examines the film's methods, style, and structure; theorizes the accessing of memory in an important photographic antecedent to this work; and explores aspects of the landscape tradition in the Canadian experimental documentary.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.676
Threshold uncertainty score0.652

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.009
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.034
GPT teacher head0.228
Teacher spread0.194 · 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 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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