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Record W2087207950 · doi:10.5751/es-05146-170333

Urban Ecology in Cape Town: South African Comparisons and Reflections

2012· article· en· W2087207950 on OpenAlexvenueno aff
Sarel S. Cilliers, Stefan J. Siebert

Bibliographic record

VenueEcology and Society · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsnot available
FundersUniversity of Cape Town
KeywordsCapeGeographyEcologyUrban ecologyEnvironmental resource managementNature ConservationArchaeologyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Little urban ecological research has been done in South Africa. The papers in the Ecology and Society special feature Urban Ecological and Social-Ecological Research in the City of Cape Town make, therefore, an important contribution to the development of urban ecology locally and globally. Different approaches have been used in the study of urban ecology of different urban areas in South Africa. Cape Town is situated in a biodiversity hotspot and is the only South African city which includes a national park. As a result the urban ecological studies were mainly driven by urban nature conservation concerns. In other cities such as Durban, open space planning and environmental management were the major issues which focused ecological studies on urban areas whereas other studies of urban areas in the Eastern Cape and North-West provinces included private and public open spaces and man-made habitats. We reflect on the Cape Town studies in a South African context and highlight conservation of biodiversity, protection of ecosystem services, management of control measures, and the conflict between humans and nature. A brief synthesis has also been given of South African urban ecological research in general.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.664

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)0.0010.000

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 head0.017
GPT teacher head0.244
Teacher spread0.227 · 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.

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

Citations46
Published2012
Admission routes1
Has abstractyes

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