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Record W3128993333 · doi:10.3390/land10020153

Bird Diversity Unconsciously Increases People’s Satisfaction with Where They Live

2021· article· en· W3128993333 on OpenAlexaffabout
Lauren Hepburn, Adam C. Smith, John M. Zelenski, Lenore Fahrig

Bibliographic record

VenueLand · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsEnvironment and Climate Change CanadaCarleton University
Fundersnot available
KeywordsNeighbourhood (mathematics)HappinessGeographyDiversity (politics)FeelingLife satisfactionEcologyPsychologySocioeconomicsSocial psychologySociologyBiology

Abstract

fetched live from OpenAlex

There is growing evidence that exposure to nature increases human well-being, including in urban areas. However, relatively few studies have linked subjective satisfaction to objective features of the environment. In this study we explore the links among objective environmental features (tree cover, water, and bird diversity) and subjective judgements of satisfaction. We surveyed residents of Ottawa, Canada (n = 1035) about their satisfaction with their local neighbourhoods. We then compared the survey responses to measures of nature near their homes, including bird diversity (number of bird species), tree canopy cover, and distance to water. After controlling for effects of income and subjective happiness, residents’ neighbourhood satisfaction was positively related to the number of bird species nearby, even before participants were prompted to consider nature. Residents’ appreciation of their local neigbourhood relative to others also increased with tree canopy cover and nearness to water. Unsolicited comments from participants following the survey indicated that while residents consciously appreciate trees and water, the relationship between bird diversity and neighbourhood satisfaction appears to be unconscious; very few of the participants mentioned birds. Based on these results, we speculate that a diverse local bird community may provoke feelings of satisfaction through their presence, activity, and songs. Our results create a compelling argument for city planners and individual residents to maintain bird-friendly spaces in urban areas.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: yes
Observationalhigh
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: yes
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.082
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.202
Teacher spread0.194 · 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

Labeled directly by 2 models reading the full record.

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

Citations30
Published2021
Admission routes2
Has abstractyes

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