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Record W6998647940

The Animation of Canadian Culture: Norman McLaren and the National Film Board

2023· book-chapter· en· W6998647940 on OpenAlexaboutno aff

Bibliographic record

VenueArchivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) · 2023
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsnot available
Fundersnot available
KeywordsAnimationMovie theaterGeniusDiversity (politics)StudioCode (set theory)
DOInot available

Abstract

fetched live from OpenAlex

There is no worse title one could attribute to McLaren, as the press at times do nowadays, than “the Walt Disney of Canada”, which is understandable only as an attempt to attribute a genius comparable to that of Disney to McLaren. In fact, nothing makes him comparable to the “Wizard of Burbank”, indeed in many aspects McLaren represents to opposite of the Disney model (and American model generally) based on the mass production of animated cartoons. We may even interpret McLaren’s efforts to use the technical and expressive diversity of the NFB animation films as a stylistic code oriented to the intentional research into the non-standardisation with the dominant model in this field: the American cartoon. McLaren interpreted his own appointment to public service by making animated films at the NFB, starting from his own cinema, the “metaphor” of an irreducible identity, where not only the most diverse experiences and identities of animation live together but where every author is invited to experiment and dialogue with the other languages. In his research into animation cinema McLaren experimented and studied above all the specific nature of this medium: because animation cinema does not reproduce movement, it creates it.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.944
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.030
GPT teacher head0.246
Teacher spread0.216 · 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 teacher head, not a consensus.

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
Published2023
Admission routes1
Has abstractyes

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