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Record W4367157192 · doi:10.7202/1092576ar

Little Orphans. Directed by Ruth Lawrence; written by Emily Bridger; produced by Jennifer Hawley, Sherry White. Imagine That Productions, 2020

2022· article· en· W4367157192 on OpenAlexaffvenueabout
Jamie Skidmore

Bibliographic record

VenueNewfoundland and Labrador Studies · 2022
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsWhite (mutation)ArtArt historyHistoryBiology

Abstract

fetched live from OpenAlex

Little Orphans. Directed by Ruth Lawrence; written by Emily Bridger; produced by Jennifer Hawley, Sherry White. Imagine That Productions, 2020. Un article de la revue Newfoundland and Labrador Studies (Volume 36, numéro 2, 2021, p. 171-344) diffusée par la plateforme Érudit.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.963
Threshold uncertainty score0.676

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.5260.433

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 head0.023
GPT teacher head0.320
Teacher spread0.297 · 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.

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
Published2022
Admission routes3
Has abstractyes

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