MétaCan
Menu
Back to cohort
Record W3034228182 · doi:10.1080/13504622.2020.1776844

When screens replace backyards: strategies to connect digital-media-oriented young people to nature

2020· article· en· W3034228182 on OpenAlexaff
Rachael C. Edwards, Brendon M. H. Larson

Bibliographic record

VenueEnvironmental Education Research · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNarrativePsychological interventionAppealMedia literacyDigital mediaPublic relationsSociologyMedia studiesPolitical scienceAdvertisingPsychologyBusiness

Abstract

fetched live from OpenAlex

Children’s connection to nature (CTN) is declining with each generation, a concerning trend given that CTN is positively linked to wellbeing and environmentalism. A primary cause of this decline is that twenty-first-century youth engage with screens for several hours each day, which to a large extent replaces nature-based play. Researchers have proposed that this change represents a transition in human orientation, particularly in Westernized societies, from nature (biophilia) to digital media (videophilia). Interventions promoting nature-based play must acknowledge digital-media use as a competing leisure pursuit, but the literature presents little guidance for designing programs that will attract young people who are more oriented toward digital media than nature. Drawing on a wide breadth of research, we address this gap through (1) exploring the implications of videophilia for nature-based programming and (2) summarizing recommendations from a narrative literature review for designing interventions that appeal to digital-media-oriented youth.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.015

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 head0.025
GPT teacher head0.331
Teacher spread0.306 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations108
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueEnvironmental Education ResearchSame topicUrban Green Space and HealthFrench-language works237,207