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Record W4282932917 · doi:10.1139/er-2021-0107

A selective review of environmental perceptions, attitudes, place attachment, and their spatial characterisation: contrasting the South African and global perspectives

2022· review· en· W4282932917 on OpenAlexvenueno aff
Simangele Dlamini, Solomon G. Tesfamichael, Tholang Mokhele

Bibliographic record

VenueEnvironmental Reviews · 2022
Typereview
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsPerceptionHuman geographyGlobal SouthIdentity (music)Space (punctuation)SociologyGeographyEconomic geographyEnvironmental ethicsRegional sciencePolitical sciencePsychology

Abstract

fetched live from OpenAlex

This selective review points to a rich body of literature on environmental perceptions, attitudes, and place attachment in South Africa. Research works highlight that the global-North dominates in human–nature relations studies, with relatively less work done in less developed economies such as sub-Saharan Africa and South Africa. Additionally, the review of the literature on these concepts points to the complexity of these aspects in terms of their conceptual distinctions, amorphous nature, and hence the difficulties surrounding their spatial characterisation. This selective review aims to provide a contrast between South African and international studies on these concepts. This review notes that human–nature studies in South Africa are dominated by place research, which is largely influenced by the country's spatio-political setting, where social engineering was influenced by past policies that had substantial impacts on the arrangement of space, identity, and belonging. Additionally, the review notes the dearth of literature that has attempted to spatially characterise human–nature relations in the country. Spatially characterising these concepts could be beneficial for urban and environmental planners and policymakers in the country, and assist in initiatives meant to reduce spatial inequalities in the country.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.031
GPT teacher head0.298
Teacher spread0.267 · 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 teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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

Citations3
Published2022
Admission routes1
Has abstractyes

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