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The Influence of External Stakeholders in Shaping Mining CSR Practices in Canada and the Philippines and their Impacts on Local Communities: A Case Study on San Roque Metals Inc. in Mindanao, Philippines

2020· article· en· W3213315198 on OpenAlexaffvenueabout
Angela Asuncion

Bibliographic record

VenueRural Review Ontario Rural Planning Development and Policy · 2020
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCorporate social responsibilityGeographySocioeconomicsBusinessPolitical scienceSociologyLaw

Abstract

fetched live from OpenAlex

As social and environmental issues become more pronounced in the mining industry, the Corporate Social Responsibility (CSR) practices of multinational enterprises and the external influences that shape these practices have become increasingly critical concepts in international business and socio-ecological discourse. CSR initiatives across the mining industry address the negative externalities of mining operations and seek to actualize the greatest social, environmental and economic benefits of the extractive sector across all stakeholders involved. However, CSR practices and their effectiveness are known to be significantly shaped by international, national and civil society institutions. Gaps in knowledge within literature identifies a lack of understanding in respect to mining company- community relations and the effectiveness of environmental CSR approaches at the local level. These findings pose the opportunity to inform Canadian mining industries, both locally and globally, of CSR frameworks that contribute towards the social and environmental resiliency of local communities.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.652

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.077
GPT teacher head0.286
Teacher spread0.209 · 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

Citations0
Published2020
Admission routes3
Has abstractyes

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