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Record W6980762022

Cops, Lies, And Videotape

2022· other· en· W6980762022 on OpenAlexaboutno aff

Bibliographic record

VenueBulletin of Miscellaneous Information (Royal Gardens Kew) · 2022
Typeother
Languageen
FieldMaterials Science
TopicMetallurgical and Alloy Processes
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousAmazon rainforestCheatingSexual misconductMisconductJournalism
DOInot available

Abstract

fetched live from OpenAlex

*A note to listeners: Today's episode deals with sexual violence inflicted on Indigenous minors and won't be suitable for all listeners.In 2006, RCMP Const. Joseph Kohut kicked down the door to his ex's home in Prince George, B.C., and left with certain belongings. His ex said that one of the things Kohut took was a videotape showing him sexually harassing an underage Indigenous girl. Kohut had already been investigated for sexual misconduct after a local judge pled guilty to sexually assaulting several Indigenous minors. Kohut's ex, also a Mountie, reported the alleged theft of evidence. So what happened next? Reporter Jessica McDiarmid tells the story of 16-years of entropy and indifference within the RCMP. Host: Jesse BrownCredits: Tristan Capacchione (Audio Editor and Technical Producer)Guest: Jessica McDiarmid Further reading: Toronto Star investigation, by Jessica McDiarmid Sponsors: Oxio, Rakuten, Freshbooks If you value this podcast, Support us! You'll get premium access to all our shows ad free, including early releases and bonus content. You'll also get our exclusive newsletter, discounts on merch at our store, tickets to our live and virtual events, and more than anything, you'll be a part of the solution to Canada's journalism crisis, you'll be keeping our work free and accessible to everybody. You can listen ad-free on Amazon Music-included with Prime. Hosted on Acast. See acast.com/privacy for more information.

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)0.005
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.139
Threshold uncertainty score0.466

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1390.048

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 head0.006
GPT teacher head0.179
Teacher spread0.173 · 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
Published2022
Admission routes1
Has abstractyes

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