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Record W2181422939 · doi:10.5539/jpl.v8n4p185

Challenges Posed on The New Mining Act and Its Regulations in Tanzania

2015· article· en· W2181422939 on OpenAlexvenueno aff
Charles W. Marwa, Isabela Warioba

Bibliographic record

VenueJournal of Politics and Law · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Issues in South Africa
Canadian institutionsnot available
Fundersnot available
KeywordsTanzaniaEnforcementBusinessCorporate governanceOrder (exchange)Scale (ratio)EvictionSustainable developmentIndigenousLaw enforcementEnvironmental planningLawPolitical scienceFinanceGeography

Abstract

fetched live from OpenAlex

<p>This paper assesses the challenges that are posed to the new mining law and other Regulations that govern the mining sector in Tanzania. The main issues discussed in this paper include the conflicts between the local people and the mining companies regarding land ownership, compensation and forced eviction, conflicts between Small Scale Mining (SSM) and Large Scale Mining (LSM).</p><p>The findings obtained by the authors, intimates that the major problems in the mining sector are due to lack of law enforcement and good governance in the sector as well as lack of awareness of the laws governing the sector by the local communities.</p>Lastly, the authors concludes and recommend that, until and unless the laws are adhered to and kept into practice, the problems in the mining sector will not be easily resolved. Hence in order for the mining sector to benefit the indigenous and the investors, there should be enhancement of sustainable development;, people should be educated on the laws and the effects of mining on the environment and the relationship between SSM and LSM be improved.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.841
Threshold uncertainty score0.105

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.093
GPT teacher head0.346
Teacher spread0.253 · 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 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

Citations6
Published2015
Admission routes1
Has abstractyes

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