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Record W3016610625 · doi:10.5260/chara.21.4.27

Films on Demand Master Academic Video Collection

2020· article· en· W3016610625 on OpenAlexaboutno aff
Lizah Ismail

Bibliographic record

VenueThe Charleston Advisor · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Subject (documents)EntertainmentCorporationVariety (cybernetics)SociologyAdvertisingMultimediaMedia studiesBusinessWorld Wide WebComputer scienceVisual artsHistoryArt

Abstract

fetched live from OpenAlex

Streaming media has reached a ubiquitous threshold, easily accessible in a variety of platforms for the general consumer in pursuit of entertainment. Streaming media in the educational context is not far behind. Films on Demand Master Academic Collection (FODMAC), an Infobase product (<<ext-link ext-link-type="uri" xlink:href="https://www.infobase.com/">https://www.infobase.com/</ext-link>>), is a popular option for many academic institutions. FODMAC’s content partners include many highly acclaimed and award- winning content producers such as PBS, BBC, TED, Bill Moyers, ABC, NBC, the Canadian Broadcasting Corporation, National Geographic, HBO Documentary Films, and Films for the Humanities and Sciences and features over 1,000 subject categories from 25 core academic subject areas that range from Anthropology to Engineering, Health and Medicine to Music and Dance, and Business and Economics to World Languages. Ease of access and convenient features such as sharing, customizable playlists and embedment in course management systems and other digital platforms make FODMAC a competitive resource as demand in educational streaming media grows.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.003

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 head0.074
GPT teacher head0.238
Teacher spread0.164 · 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
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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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