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Record W7043891398

Towards community benefits derived from mining : assessing the potential role of community development agreements in Zimbabwe

2023· other· en· W7043891398 on OpenAlexaboutno aff

Bibliographic record

VenueUpSpace Institutional Repository (University of Pretoria) · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenizationIndigenousEmpowermentCommunity developmentDeveloping countryPosition (finance)Mining industryIncentive
DOInot available

Abstract

fetched live from OpenAlex

Mining is a significant economic contributor in both developing and developed countries. The industry is responsible for the creation of cities, communities, industries, employment, and infrastructure. Although mining has positive economic benefits, there are negative social, economic, and environmental consequences of mining. There are host communities that are yet to see the benefits of mining activities. This has placed community development in mining areas at discussions of the benefits of mining outside the economy. Zimbabwe as a developing country has placed mining at the centre of its development agenda. With the industry receiving investments. This begs the question of whether communities will receive equitable benefits from continued mining operations. To address the issue of community development, Zimbabwe enacted the Indigenisation and Economic Empowerment Act. With the aim of providing measures for the economic empowerment of indigenous Zimbabweans. This was to be achieved by ensuring that indigenous Zimbabweans had a controlling stake in businesses. To this end community share ownership trusts were promulgated into the indigenisation laws. These trusts were to receive a 10% ownership share in mining businesses and financial pledges to capitalize the trusts. The success of CSOTs has been a mixed bag with most of the CSOTs non-functional. With the amendments to the Indigenisation laws, the legal position of CSOT is not clear. This study examines the potential of community development agreements (CDAs) as a tool that ensures communities receive equitable benefits. It investigates this potential by analysing the Zimbabwean legal framework. It looks at CDA as a tool that might be utilized in Zimbabwe by looking at the advantages and disadvantages of CDAs. This also includes examining how other jurisdictions have adopted CDAs. In countries such as Australia and Canada, the negotiation of CDAs has become standard practice for all new resource development projects. This study will examine the approaches taken by Australia, Canada, and South Africa into incorporating CDAs into their frameworks.

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)0.004
metaresearch head score (Gemma)0.012
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 score0.071
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0040.004
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.248
Teacher spread0.217 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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