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Record W4400791730 · doi:10.1515/9780228021612

The Interactive Documentary in Canada

2024· book· en· W4400791730 on OpenAlexaboutno aff

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2024
Typebook
Languageen
FieldSocial Sciences
TopicMultimedia Communication and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Interactive documentary emerged rapidly from a constellation of changing technologies and practices to much excitement, yet its history is short and its future uncertain. In the mid-2010s Canada was a world leader in the creation of i-docs. Less than a decade later technological obsolescence has rendered many of these celebrated projects inaccessible, while rapid digital innovation continues to change the i-doc form and its modes of experience. The Interactive Documentary in Canada captures this transitional moment in documentary filmmaking and media production. Bringing together a range of historical, theoretical, and critical approaches, this collection examines the past – and the imagined future – of a nonfiction storytelling phenomenon that has Canadian institutions, figures, and works at its centre. Embracing a polyphonic conception of interactive documentary, the volume includes explorations of web-based, app-based, installation, and virtual reality works that push the boundaries of what is understood as documentary cinema. Leading documentary scholars and makers consider the historical and technological contexts of i-doc production, innovation, and exhibition; the political and pedagogical potential of the genre; the ethics of the i‐doc experience; and the format’s future lifespan in the contemporary media landscape. The Interactive Documentary in Canada establishes a place for the i-doc in the history of Canadian film, highlighting the genre’s significant impact on the National Film Board of Canada and on contemporary global documentary media.

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)0.004
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 score0.083
Threshold uncertainty score0.600

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0180.008
Scholarly communication0.0140.003
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0340.002

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 head0.013
GPT teacher head0.244
Teacher spread0.231 · 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
Published2024
Admission routes1
Has abstractyes

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