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Record W2129907761 · doi:10.1177/0013916512451901

Happiness and Feeling Connected

2012· article· en· W2129907761 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.

Bibliographic record

VenueEnvironment and Behavior · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsCarleton University
Fundersnot available
KeywordsHappinessSocial connectednessSocial psychologyPsychologyFeeling

Abstract

fetched live from OpenAlex

Subjective connection with nature, or nature relatedness, is similar to other environmental worldview measures in predicting sustainable attitudes and behaviors, yet is unique in predicting happiness. In two studies, the authors assessed the overlap between nature relatedness and other subjective connections (e.g., with friends or country) and examined these connections as a possible confound in explaining the link between nature relatedness and happiness. Study 1 adapted a measure of general connectedness and administered it to student ( n = 331) and community ( n = 415) samples along with multiple nature relatedness and happiness indicators. Study 2 examined more established measures of subjective connections in another community sample ( n = 204). General connectedness predicted happiness well, yet nature relatedness remained a significant distinct predictor of many happiness indicators, even after controlling for other connections. Results support the notion that nature relatedness could be a path to human happiness and environmental sustainability, though confirming this causal direction requires additional research.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.999

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)0.0020.000

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 head0.020
GPT teacher head0.234
Teacher spread0.215 · 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