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Record W6927622796 · doi:10.3390/challe14010003

Towards Youth-Centred Planetary Health Education

2023· article· en· W6927622796 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueChallenges · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsYork University
Fundersnot available
KeywordsNucleofectionPretextWork (physics)Articular cartilage damageGestational periodTSG101

Abstract

fetched live from OpenAlex

This paper presents data and analyses from our Planetary Health Film Lab (PHFL) and its sister project the Youth Climate Report. Qualitative data include semi-structured interviews with youth and their educators and content analysis of films produced by young people (ages 19–25) from six countries (Australia, Columbia, Ecuador, Italy, India, Canada). The educative processes designed for the Planetary Health Film Lab are illustrative of our work to build the field of planetary health education that is with/for young people whose educative projects are mobilized in turn to educate wider audiences and for policy change. The analyses show how youth document and record planetary health concerns alongside responsive projects that are embedded in awareness of climate justice and their interconnected ecological systems. The qualitative content analyses of selected films resulted in three themes: (1) Anthropogenic footprints, (2) Ecological and climate justice, and (3) Collective local/global solutions. Data also illustrates how young people’s participation in educative film projects contribute to the education of others and address related intergenerational justice issues. Implications for the knowledge, ethics and practices of youth-centred planetary health education are discussed as they augment the Framework for Planetary Health. Youth are crucial but overlooked collaborators in redressing planetary health education, an error we begin to correct through transdisciplinary approaches with/for young people who could help define the field.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.623
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.773
GPT teacher head0.496
Teacher spread0.277 · 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