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Record W4238632287 · doi:10.17742/image.onf.6-2.2

La mise en patrimoine sur ONF.ca

2015· article· fr· W4238632287 on OpenAlexvenueno aff
Michèle Garneau

Bibliographic record

VenueImaginations Journal of Cross-Cultural Image Studies · 2015
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

RésuméCe texte propose une approche à la fois descriptive, analytique et critique de la très active production patrimoniale actuellement en cours sur ONF.ca. En se donnant comme mission de rendre accessible son patrimoine audiovisuel, l’Office se soucie d’en orienter la réception, de proposer aux internautes l’histoire de son action audiovisuelle depuis sa fondation en 1939. Par le relevé d’un certain nombre de valeurs exhibées (authenticité, représentativité, renommée et proximité), et de registres privilégiés (dont celui de la commémoration), l’auteur tente de circonscrire une axiologie du patrimoine sur ONF.ca. Dans sa seconde partie, le texte se consacre à la question de l’articulation (et de l’écart) entre mémoire patrimoniale et mémoires particulières (des films) afin de mieux cerner les contours politiques et les enjeux idéologiques de l’encadrement discursif des collections. AbstractThis article offers a descriptive, analytical and critical approach to the very active production of audiovisual heritage currently underway at NFB.ca. Designed to make the National Film Board (NFB)’s audiovisual heritage more accessible, the website carefully guides its users through the history-memory of audiovisual production at the Film Board from its foundation in 1939 through to the present. By analyzing how the website showcases its films, endorsing specific values (authenticity, representativeness, recognition and proximity) and privileging certain registers (such as commemoration), the article first attempts to define an axiology of heritage in NFB.ca. The article then focuses on questions of the articulation of (and the variation between) history-memory and particular memories (of films) in order to better outline the political contours and ideological stakes of the discursive framework of the NFB’s collections.

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)0.010
metaresearch head score (Gemma)0.051
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.747
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.051
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0010.021
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.165
GPT teacher head0.565
Teacher spread0.400 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2015
Admission routes1
Has abstractyes

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