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Film Guilds and Unions

2021· reference-entry· en· W4206134672 on OpenAlexaboutno aff

Bibliographic record

VenueCinema and Media Studies · 2021
Typereference-entry
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCraftGuildFilm industryHollywoodScholarshipCollective bargainingPolitical scienceNegotiationStudioAlliancePublic relationsLawMovie theaterHistoryVisual artsArt

Abstract

fetched live from OpenAlex

Film guilds and unions engage in collective bargaining on behalf of media workers in the United States and around the world. Historically, the word “guild” was associated with craft and professional training, but in the US film industry it is often interchangeable with “union.” The exception to this rule is the Producers Guild of America (PGA), which is a professional organization that maintains professional standards and provides its members with networking opportunities. In Hollywood, unions also exist alongside craft organizations such as the American Society of Cinematographers, which help to advance the art and establish professional norms, but do not negotiate wages or provide health and retirement benefits. Some film unions (such as those in the United States, Canada, and England) are historically more well established, in contrast to nations where production is not unionized or unionization has only recently begun. Film unions and guilds in the United States, which include the Directors Guild of America (DGA), the International Alliance of Theatrical Stage Employees (IATSE), SAG-AFTRA (the union that represents screen performers), and the Writers Guild of America (WGA), have been the most well-studied. Since the first Studio Basic Agreement in 1926, unions have contributed to the professional development and well-being of Hollywood workers, but they have historically been marginal institutions within cinema and media scholarship. There has been abundant writing on union activities in journalistic sources and union magazines, all of which are essential reading for scholars of film guilds and unions. Those looking for scholarship on unions and guilds will need to read across disciplines, as the work on film guilds and unions is methodologically diverse and comes from labor historians and political economists of communication, in addition to cinema and media scholars.

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)0.004
metaresearch head score (Gemma)0.020
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.055
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0240.017
Scholarly communication0.0150.010
Open science0.0010.011
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0550.005

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 head0.270
Teacher spread0.196 · 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 routes1
Has abstractyes

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