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Record W3207586296 · doi:10.24908/ijesjp.v8i2.15147

Interview: Waste, After the Revolution

2021· article· en· W3207586296 on OpenAlexvenueno aff
A Riccio, Andrea Haverkamp

Bibliographic record

VenueInternational Journal of Engineering Social Justice and Peace · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse academic and cultural studies
Canadian institutionsnot available
Fundersnot available
KeywordsReadabilitySpace (punctuation)Media studiesHost (biology)SociologyAestheticsArtLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Laborwave Radio and Opening Space for the Radical Imagination present an interview between podcast host Alex Riccio and Andrea Haverkamp recorded as part of our series After the Revolution. This podcast and interview series is inspired by a desire to offer more than a diagnosis of what is wrong with today, by further focusing on what we might be able to bring about. We begin by highlighting the importance of considering one feature of society than imagining what it might look like after the revolution, and finally offering some ideas on how get to this revolutionary society. This paper is the transcript of the interview with edits for readability.

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)0.002
metaresearch head score (Gemma)0.014
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: none
Teacher disagreement score0.039
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0130.003
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0390.010

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 head0.024
GPT teacher head0.228
Teacher spread0.205 · 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
Published2021
Admission routes1
Has abstractyes

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