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Record W4388780529 · doi:10.1515/9781552385074

Spirit Matters

2009· book· en· W4388780529 on OpenAlexaboutno aff
Geoffrey Simmins

Bibliographic record

VenueUniversity of Calgary Press eBooks · 2009
Typebook
Languageen
FieldArts and Humanities
TopicIndian and Buddhist Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiology

Abstract

fetched live from OpenAlex

Ronald Spickett (1926- ) is a Calgary-based artist, poet, and Zen Buddhist lay priest. During his long career, he also taught studio art, both at the Alberta College of Art and Design and at the University of Calgary. Today, Ronald Spickett, also known by his Buddhist name of Gyo-Zo, is best known for a series of ambitious paintings he executed during the 1960s, paintings with Western themes such as posses and riders. However, the scope of Spickett's work proved to be much more diverse and includes genre paintings, landscapes, non-representational paintings, sculptures, and paintings with religious and spiritual themes. The artist's work, as Simmins' study shows, is not easily pigeon-holed; Spickett is more than a Western artist, more than a Buddhist artist, more than simply the sum of his paintings. Rather, Simmins argues, he is an "ideas-based" artist whose work reveals complexities and undercurrents that link him with the prevailing artistic currents of his times, yet also testify to his originality and unique style. Simmins was granted complete access to the artist's personal and professional papers and interviewed him on numerous occasions. Thus the artist's own statements on his life and work make an invaluable contribution to Spirit Matters: Ron (Gyo-zo) Spickett, Artist, Poet, Priest, and are considered alongside critical writings, broader studies in Canadian art history, and still larger currents in Canadian artistic and intellectual life.

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)0.003
metaresearch head score (Gemma)0.012
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.105
Threshold uncertainty score0.351

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0070.010
Scholarly communication0.0130.009
Open science0.0010.009
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.1050.051

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 head0.025
GPT teacher head0.171
Teacher spread0.146 · 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
Published2009
Admission routes1
Has abstractyes

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