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Record W7162202995 · doi:10.59236/emro.v25i8a8036

Fight Like Hell

2023· article· W7162202995 on OpenAlexaboutno aff
Alexander Rolfe

Bibliographic record

VenueEducational Media Reviews Online · 2023
Typearticle
Language
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBattlePublicityMovie theaterState (computer science)ClothingHollywoodImmigration

Abstract

fetched live from OpenAlex

Distributed by Bullfrog Films, PO Box 149, Oley, PA 19547; 800-543-FROG (3764)Produced by Martha Gregory and Ian CheneyDirected by Ian Cheney2023, Streaming, 55 mins Kaiulani Lee gives a convincing and moving monologue as Mother Jones, recounting her struggles on behalf of miners and child workers. Her portrayal is very convincing; the production is well-acted, well-written, and well-researched. Some of it is too grim for children, but for high school students and beyond it would be a great accompaniment to a study of American labor history, and one they would probably remember for a long time. The culmination of the film is Mother Jones's role in West Virginia's Battle of Blair Mountain, but she covers the significant parts of her life in getting there. She lost her family to yellow fever, lost her few possessions in the Great Chicago Fire, and emerged from obscurity and hardship to play an important role in some of the most tumultuous times of American history. She brought considerable publicity to the plight of children working in clothing factories and led them on a march to FDR's Long Island home. She exhorted miners to demand their rights and urged them to unionize and strike in state after state. The film contains many of her famous lines and recounts her defeats as well as her victories. Recommended for any collection supporting labor history or American history. Awards:Best Women's Film, Washington DC International Cinema Festival; Best Actress in a Feature Film, Crown Point International Film Festival; Best Actress, Toronto International Women Film Festival

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)0.001
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.160
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.043

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 head0.095
GPT teacher head0.315
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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes1
Has abstractyes

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