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Introduction

2022· book-chapter· en· W4297132086 on OpenAlexaboutno aff
Davies Jonathan S., Ismael Blanco, Adrián Bua, Ioannis Chorianopoulos, Mercè Cortina-Oriol, Andrés Feandeiro, Niamh Gaynor, Brendan Gleeson, Steven Griggs, Pierre Hamel, Hayley Henderson, David Howarth, Roger Keil, Madeleine Pill, Yunailis Salazar, Helen Sullivan

Bibliographic record

VenuePolicy Press eBooks · 2022
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAusterityTheme (computing)Media studiesLibrary scienceSociologyHistoryGeographyPolitical scienceRegional scienceComputer scienceLawWorld Wide Web

Abstract

fetched live from OpenAlex

The introductory chapter explains the nature of the research, the reasons for focusing on the theme of collaboration, and introduces the concept of austerity. It introduces the eight cities of Athens, Baltimore, Barcelona, Dublin, Greater Dandenong (Melbourne), Leicester, Montreal and Nantes and explains the book structure.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.439
Threshold uncertainty score0.800

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.4390.238

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 head0.067
GPT teacher head0.341
Teacher spread0.274 · 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.

Study designNot applicable
Domainnot available
GenreEditorial

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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