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Record W4297265907 · doi:10.1080/09540261.2022.2126297

“Not about us without us” – the feelings and hopes of climate-concerned young people around the world

2022· article· en· W4297265907 on OpenAlexaff
James Diffey, Sacha Wright, Jennifer Uchendu, Shelot Masithi, Ayomide Olude, Damian Omari Juma, Lekwa Hope Anya, Temilade Salami, Pranav Reddy Mogathala, Hrithik Agarwal, Hyunji Roh, Kyle Villanueva Aboy, J. Allan Cote, Aditiya Saini, Kadisha Mitchell, Jessica Kleczka, Nadeem Gomaa Lobner, Leann Ialamov, Monika Borbely, Tupelo Hostetler, Alaina Wood, Aoife Mercedes Rodriguez-Uruchurtu, Emma Lawrance

Bibliographic record

VenueInternational Review of Psychiatry · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsYork University
Fundersnot available
KeywordsFeelingPoliticsHumanityAffect (linguistics)PsychologyClimate changeMental healthWork (physics)Social psychologyPolitical sciencePsychotherapistLaw

Abstract

fetched live from OpenAlex

The feelings and hopes of young people around the world are often neglected in policymaking and research, with consequences for both their wellbeing and the effectiveness of humanity's response to the climate crisis. Many of them are distressed by climate change's impacts, the inaction of political and corporate leaders, the ways other people respond to their feelings, and the lack of support they have to share their feelings or get involved in meaningful climate-related work. This paper is written by a group of twenty-three concerned young people from fifteen countries. It provides a first-hand account of our deepest feelings, how these feelings affect our daily lives, the support we want to help us cope, and our hopes for a radically more compassionate future. The results are particularly relevant to policymakers, mental health professionals, journalists, educators, and people working with young people more widely.

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)0.006
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.006
Scholarly communication0.0060.004
Open science0.0000.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.111
GPT teacher head0.424
Teacher spread0.312 · 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 designQualitative
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

Citations73
Published2022
Admission routes1
Has abstractyes

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Same venueInternational Review of PsychiatrySame topicClimate Change Communication and PerceptionFrench-language works237,207