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Record W4407959003 · doi:10.5771/9780761848684

Someone Out There Is Listening

2009· book· en· W4407959003 on OpenAlexaboutno aff
Ed Petkus

Bibliographic record

VenueHamilton eBooks · 2009
Typebook
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningPsychologyCommunication

Abstract

fetched live from OpenAlex

Someone Out There is Listening tells the story of Eddie Hazell, a jazz guitar player and vocalist with a unique style unmatched in the last half century. Hazell had a combination of good looks, skills, and style. He was a '50s guy - heady, hopeful, and a believer in the system even though it didn't always work for him. As a rising star, Hazell had great bookings across the country and Canada. He was compared to some of the top stars in the music business, columnists and critics gave him solid reviews and high praise for his performances, and disc jockeys played his recordings and were eager for more. People who knew him had no doubt that he would make the big time - it was only a matter of when. Eddie Hazell's story is about the times and the vicissitudes of the music business, and what it took to accomplish one's goals. Eddie strove not only for success, but to persevere during bad times and personal hardships, while still maintaining artistic integrity and enjoyment of life. Eddie Hazell went the full mile; he didn't leave anything out. The celebrated music producer George Martin once said: 'The music business is littered with shooting stars that burned out. So pace yourselves; it's not a sprint. It is more like a marathon. Remember you have to keep running.' Eddie Hazell's life is a musical marathon - reading about it is like running with him and the many other runners in his field.

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)0.007
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 score0.124
Threshold uncertainty score0.415

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0190.005
Scholarly communication0.0100.007
Open science0.0010.010
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.1240.039

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 head0.037
GPT teacher head0.211
Teacher spread0.174 · 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
Published2009
Admission routes1
Has abstractyes

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