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Record W4247693171 · doi:10.32920/ryerson.14664276.v1

Documenting the world at home and abroad : The Jacques Madvo collection

2021· preprint· en· W4247693171 on OpenAlexaffabout
Alexandra Jokinen

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsToronto Metropolitan University
FundersDurham University
KeywordsAmateurLift (data mining)Value (mathematics)Perspective (graphical)Data collectionMedia studiesVisual artsAdvertisingArtSociologyHistoryComputer scienceBusinessSocial scienceArchaeology

Abstract

fetched live from OpenAlex

This thesis draws on the cataloguing and examination of the Madvo Collection at the Liaison of Independent Filmmakers of Toronto (LIFT) as the basis to determine the value of his independent non-fiction films and resolve possible scenarios for their preservation. The collection contains 240 canisters of 16mm non-fiction films and production elements that LIFT intends to use as a resource for found footage films. This raises several concerns for the future of the materials, the most critical of which is the physical destruction of the films. This thesis aims to create a record of Madvo’s oeuvre so that his work can be protected from LIFT’s claim to use it as found footage. It offers different uses for the materials, as well as a broader perspective on the cultural value of the collection, paying particular attention to its importance for the history of amateur films and home movies.

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)0.006
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 score0.230
Threshold uncertainty score0.457

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.007
Science and technology studies0.0060.002
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.024
GPT teacher head0.244
Teacher spread0.220 · 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
Published2021
Admission routes2
Has abstractyes

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