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Record W2038803375 · doi:10.1093/spp/37.8.638

The case against growth

2010· article· en· W2038803375 on OpenAlexaffabout
S. Mendritzki

Bibliographic record

VenueScience and Public Policy · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLibrary sciencePolitical scienceMedia studiesSociologyComputer science

Abstract

fetched live from OpenAlex

Journal Article The case against growth Get access Managing Without Growth: Slower by Design, Not Disaster by Victor Peter A Edward Elgar, Cheltenham, UK and Northampton, MA, USA, 2008, 272US$28.00 (paperback), 9781848442054. Stefan Mendritzki Stefan Mendritzki Interdisciplinary Graduate Program, University of Calgary, PF 3168, 2500 University Drive NW, Calgary, Canada T2N 1N4; Email: semendri@ucalgary.ca Search for other works by this author on: Oxford Academic Google Scholar Science and Public Policy, Volume 37, Issue 8, October 2010, Pages 638–640, https://doi.org/10.1093/spp/37.8.638 Published: 01 October 2010

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)0.008
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0080.025
Scholarly communication0.0120.022
Open science0.0020.011
Research integrity0.0130.020
Insufficient payload (model declined to judge)0.0220.004

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 head0.007
GPT teacher head0.226
Teacher spread0.219 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations1
Published2010
Admission routes2
Has abstractyes

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