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Record W6921752492 · doi:10.7916/d8-zhz6-k505

Marie Dressler

2013· article· en· W6921752492 on OpenAlexaboutno aff

Bibliographic record

VenueColumbia Academic Commons (Columbia University) · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)World War IIBlacklistingHollywoodSpanish Civil WarFace (sociological concept)TrilogyPoetry

Abstract

fetched live from OpenAlex

Marie Dressler was a top star who died at the height of her popularity. Her career is thoroughly documented, and this synopsis unavoidably recounts the tireless efforts of biographies by Betty Lee and Matthew Kennedy. She remains a comedienne with a loyal following, with a foundation and museum in her birthplace of Cobourg, Ontario. In the context of women behind-the-scenes in early film production, Dressler provides an example of a failed attempt to turn stage and screen fame into an eponymous production company where she had a hand in writing the resulting two-reelers. In the mid-1910s, it was common to turn movie stardom into professional autonomy by creating an eponymous film company. Dressler’s self-produced films were the last before a well-mythologized descent into poverty and reemergence as an MGM early-sound star with the help of loyal friend, screenwriter Frances Marion. Her decline coincided with well-publicized off-screen activities including the World War I bond drive and the 1919 Actors’ Equity strike. Assertions that she was the victim of anti-union blacklisting remain unsubstantiated by her biographers Lee and Kennedy, who conclude instead that she had simply spent too much time off stage and screen, or in lackluster roles.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.028
GPT teacher head0.188
Teacher spread0.161 · 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; both teacher heads agree on what is shown here.

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
Published2013
Admission routes1
Has abstractyes

Explore more

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