MétaCan
Menu
Back to cohort
Record W2106720006 · doi:10.1177/2167696815578338

Generative Concern and Environmentalism

2015· article· en· W2106720006 on OpenAlexafffundabout
Fanli Jia, Susan Alisat, Kendall Soucie, Michael W. Pratt

Bibliographic record

VenueEmerging Adulthood · 2015
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsWilfrid Laurier University
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Windsor
KeywordsEnvironmentalismGenerativityGenerative grammarNarrativePsychologyIdentity (music)SociologyPoliticsSocial psychologyEnvironmental ethicsGender studiesAestheticsPolitical scienceLawLiterature

Abstract

fetched live from OpenAlex

In a mixed-methods longitudinal study, we examined the relationship between Erikson’s construct of generativity, measured at ages 23 and 26, and environmentalism at age 32. Over a hundred Canadian youth completed a questionnaire that measured generative concerns. Environmentalism was assessed by questionnaires on involvement, identity, and attitudes, as well as through narratives about personal experiences with the environment. Narratives were coded for meaning, vividness, and impact of environmentalism. Stronger generative concern in emerging adulthood positively predicted environmentalism after controlling for liberal political orientation and benevolence values. Qualitative analyses of the environmental narrative of participants high in generative concerns revealed three themes that highlight the developmental process that ties generative concerns to environmentalism: (1) wanting to feel more empowered to help the environment, (2) the role of having children as a focus for crystallizing environmentalism, and (3) the passing on of specific family traditions from earlier generations. Environmentalism thus may be one important domain of expression for generative care in 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 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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.327
Teacher spread0.282 · 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 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

Citations55
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueEmerging AdulthoodSame topicIdentity, Memory, and TherapyFrench-language works237,207