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Record W4210640398 · doi:10.1515/9780804777537-001

Preface

2020· book-chapter· en· W4210640398 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueStanford University Press eBooks · 2020
Typebook-chapter
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

w h a t y o u t h I n k o f a S h I P -h o P .I am a white, Canadian woman, who at the time of this study had recently moved to the United States to take up an academic position at a private research-intensive college.And neither is Tim. 1 Also white, he is a high school language arts teacher, a haiku poet, runner, and committed bird-watcher who self-admittedly knew nothing about rap music.This disjunction helps explain his students' surprise when Tim announced that the class would be studying hip-hop and spoken word culture in the last term of their senior year.Then he introduced me as the professor who would be coteaching the class.One student asked if he could borrow a tape-recorder, since "there's a lot going on in the school teachers don't know about," a situation he was hoping to change.The "lot" he referred to is the hip-hop poetry, including individual and group (or cipher) improvised freestyling and rapping, which pervades the hallways of urban high schools across the United States but is rarely invited into classrooms.Which doesn't mean that popular culture, and in this case hip-hop, isn't already present in schools, shaping the identities of students and therefore how, what, and why they learn.Tim teaches English, specializing in creative writing, in an urban arts magnet high school in a midsized city in the northeastern United States.In the fall of 2001, I was an assistant professor in a local university's faculty of education.The university suffers from the elitist reputation problems of similar private institutions located in poor urban centers.I had been studying, in theory, the implications of spoken word and hip-hop culture for youth identities and language practices.I met Tim, and he asked me to help him develop and teach a curriculum grounded in hip-hop culture in two of his senior classes.He had been teaching English and creative writing in the city school district for more than twenty years and felt that his ignorance about

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.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.951
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.050
GPT teacher head0.191
Teacher spread0.142 · 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