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Record W2056073532 · doi:10.2495/sdp-v1-n4-443-450

To control or not to control

2006· article· en· W2056073532 on OpenAlexvenueno aff
Gretha Steenkamp, Juan Steyn

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsControl (management)Environmental planningEnvironmental scienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

During 1994 and 1999, the Bloemfontein Municipality amalgamated with five other municipalities to form the Mangaung Municipality.The Mangaung Municipality now has a population of approximately 740,000 and covers an area of 6,363 km 2 .Some areas are totally urban; while in others, people live in informal settlements.The unemployment rate is 35%, but in some areas it has risen to as high as 48%.Poor people in the city cannot afford to buy burnt bricks from the major suppliers of bricks.Therefore, informal brickyards were established all over the areas where clay and/or water were available.These brickyards are now producing good homemade burnt bricks and are creating jobs in a sea of unemployment.However, the problem is that from a planning and sustainability viewpoint, all is not well.Although the location of the brickyards has brought about a saving in costs related to the transportation of bricks from the formal brickyards, of which the nearest is 300 km away, the coalburning activities of the informal brickyards create air pollution.Furthermore, no prior environmental impact studies were carried out before deciding on the location of the brickyards.Most of them have been established haphazardly in any available spot.This paper will explain how these problems could be handled within the context of sustainable planning.The environmental issues will need to be evaluated from a socioeconomic perspective.A proposed policy to guide future development will have to be part of the integrated development plan; and this paper will show how this could be effectuated in practice.

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)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.067
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0050.004
Open science0.0020.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0670.008

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 head0.021
GPT teacher head0.299
Teacher spread0.278 · 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 designTheoretical or conceptual
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

Citations0
Published2006
Admission routes1
Has abstractyes

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