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Record W7070094822

The Skin I'm In

2018· article· en· W7070094822 on OpenAlexaboutno aff

Bibliographic record

VenueYorkSpace (York University) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicRadio, Podcasts, and Digital Media
Canadian institutionsnot available
Fundersnot available
KeywordsAsideInjusticeFace (sociological concept)Skin colourSocial injustice
DOInot available

Abstract

fetched live from OpenAlex

“The Skin I’m In” is a striking, engaging and well-argued podcast transcript that questions racial equality in today’s so-called “diverse” Canada. By referring to many contemporary scholars and activists, such as bell hooks, Desmond Cole, Afua Cooper, and others, the author exposes issues that black men face daily. Aside from the author's personal experience, the transcript contains news, interviews and popular culture references that many can relate to. It creates a big picture that, once again, reminds us of the question: “For how long will this kind of injustice prevail?”

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 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 score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0090.005
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0230.006

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 head0.016
GPT teacher head0.238
Teacher spread0.222 · 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
Published2018
Admission routes1
Has abstractyes

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