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Record W4248751074 · doi:10.5040/9781501328800

Norman McLaren

2017· book· en· W4248751074 on OpenAlexaboutno aff
Nichola Dobson

Bibliographic record

VenueBloomsbury Publishing Plc eBooks · 2017
Typebook
Languageen
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsnot available
Fundersnot available
KeywordsHistoryArt

Abstract

fetched live from OpenAlex

<JATS1:p>Animator Norman McLaren is best known for his experimental films using pioneering techniques and his work as founder of the animation department of the National Film Board of Canada (NFB), but little mention is made of his Scottish heritage or his personal life. Nichola Dobson examines some of the key events and people in his life through a close examination of his key works and his personal papers, and discusses how influential they were. By using archive material to discover his personal identity and close readings of his films, Norman McLaren rediscovers one of the most important figures in animation history.</JATS1:p> <JATS1:p>Divided into thematic chapters of significant areas of influence, Dobson analyzes his formative years growing up in Scotland and his relationship with fellow Scot, John Grierson; the international travel which influenced him politically and creatively; the creative arts which played a vital part of his life; his collaborations with other artists and his complex, and rarely discussed, personal life. Each of these chapters considers his key films during those periods with a close detailed analysis and a further examination of his life through his correspondence with family and close friends. By featuring this previously un-published material, the book allows much of the consideration of the work to be in McLaren’s own words and offers a deep insight into his vast output of films over nearly 50 years.</JATS1:p>

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)0.001
metaresearch head score (Gemma)0.002
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 score0.129
Threshold uncertainty score0.430

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0060.005
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1290.052

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 head0.079
GPT teacher head0.275
Teacher spread0.196 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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