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Record W2602942253 · doi:10.3138/cjfs.25.1.27

<i>Madawaska Valley</i>: John Ormond’s Lost Film at the National Film Board of Canada

2016· article· en· W2602942253 on OpenAlexvenueaboutno aff
Kieron Smith

Bibliographic record

VenueCanadian Journal of Film Studies · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicFrench Historical and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFilmmakingEthosFilm directorPoliticsDocumentary filmCitizen journalismStorytellingMedia studiesArt historySociologyFilm studiesVisual artsArtNarrativeLiteratureMovie theaterLawPolitical science

Abstract

fetched live from OpenAlex

In 1967 Tanya Ballantyne Tree’s sensational The Things I Cannot Change marked the beginning of an influential new programme of participatory documentary filmmaking at the National Film Board of Canada. But while most accounts of Challenge for Change/Société Nouvelle (CFC/SN) trace its pared-down vérité aesthetics and ethos of audience participation to that film, few have acknowledged the significance of other, more “poetic” documentary modes being explored under the auspices of the programme in its formative days. This article takes as its focus one such film, Madawaska Valley, produced in early 1967 by a Welsh documentary filmmaker by the name of John Ormond, who was at that time on leave from his job at the BBC. Unfortunately, the film is now lost, but a production file housed at the NFB provides us with tantalizing details about the film and its reception. It suggests that The Things I Cannot Change was not the only film upon which CFC/SN tested its aesthetic and political credentials. This article explores the origins of Madawaska Valley, and argues that it too was a key foundational text in the development of a nascent CFC/SN.

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: Empirical · Consensus signal: none
Teacher disagreement score0.063
Threshold uncertainty score0.457

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0290.007
Scholarly communication0.0090.002
Open science0.0010.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.040
GPT teacher head0.205
Teacher spread0.165 · 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
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
Published2016
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Film StudiesSame topicFrench Historical and Cultural StudiesFrench-language works237,207