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Record W4205563745 · doi:10.1073/pnas.2119303118

Reply to Komatsu et al.: From local social mindfulness to global sustainability efforts?

2022· letter· en· W4205563745 on OpenAlexaff
Niels J. Van Doesum, Ryan O. Murphy, Marcello Gallucci, Efrat Aharonov‐Majar, Ursula Athenstaedt, Wing Tung Au, Liying Bai, Robert Böhm, И.Б. Бовина, Nancy R. Buchan, Xiao-Ping Chen, Kitty Dumont, Jan B. Engelmann, Kimmo Eriksson, Hyun Euh, Susann Fiedler, Justin Friesen, Simon Gächter, Camilo García, Roberto González, Sylvie Graf, Katarzyna Growiec, Serge Guimond, Martina Hřebı́čková, Elizabeth Immer-Bernold, Jeff Joireman, Gökhan Karagonlar, Kerry Kawakami, Toko Kiyonari, Yu Ru Kou, Alexandros-Andreas Kyrtsis, Siugmin Lay, Geoffrey J. Leonardelli, Norman P. Li, Yang Li, Boris Maciejovsky, Zoi Manesi, Ali Mashuri, Aurelia Mok, Karin S. Moser, Ladislav Moták, Adrian Netedu, Michael J. Platow, Karolina Raczka-Winkler, Chris Reinders Folmer, Cecilia Reyna, Angelo Romano, Shaul Shalvi, Cláudia Simão, Adam W. Stivers, Pontus Strimling, Yannis Tsirbas, Sonja Utz, Leander van der Meij, Sven Waldzus, Yiwen Wang, Bernd Weber, Ori Weisel, Tim Wildschut, Fabian Winter, Junhui Wu, Jose C. Yong, Paul A. M. Van Lange

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2022
Typeletter
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsUniversity of TorontoYork UniversityUniversity of Winnipeg
Fundersnot available
KeywordsMindfulnessModerationPsychologyIndex (typography)EconomicsSustainabilityDemographyEconometricsSocial psychologySociologyClinical psychology

Abstract

fetched live from OpenAlex

<p>Komatsu et al. (<a href="https://www.pnas.org/doi/10.1073/pnas.2119303118#core-r1">1</a>) argue that Van Doesum et al. (<a href="https://www.pnas.org/doi/10.1073/pnas.2119303118#core-r2">2</a>) may have overlooked the role of GDP in reporting a positive association between social mindfulness (SoMi) and the Environmental Performance Index (EPI) at country level. Although the relationship between EPI and SoMi is relatively weaker for countries with higher GDP, that does not imply that the overall observed relationship is a statistical artifact. Rather, it implies that GDP may be a moderator of the relationship between EPI and SoMi. The observed correlation is a valid result on average across countries, and the actual effect size would, at least to some degree, depend on GDP.<br></p>

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 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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.333
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.346
Teacher spread0.314 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2022
Admission routes1
Has abstractyes

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