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Record W2325227995 · doi:10.2118/178755-ms

Attentiveness to Community Needs and Corporate Social Responsibility in the Niger Delta Region

2015· article· en· W2325227995 on OpenAlexaff
Ebere Ellison Obisike, Justina Adalikwu-Obisike

Bibliographic record

VenueSPE Nigeria Annual International Conference and Exhibition · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsBurman University
Fundersnot available
KeywordsCorporate social responsibilityNiger deltaMultinational corporationStakeholderCorporationGovernment (linguistics)BusinessNatural resourcePublic relationsEconomic growthPolitical scienceEconomicsDeltaLaw

Abstract

fetched live from OpenAlex

Abstract Given the fact that most literature on the activities of the Oil Multinational Corporations (MNCs) in Niger Delta region focuses on corporate inattentiveness to the needs of the communities and the chronic corporate and government socioeconomic irresponsibility, this study used Stakeholder theory and critical ethnography research method to examine the relationship between attentiveness to the needs of communities in the Niger Delta region and Corporate Social Responsibility (CSR). While acknowledging that CSR has several definitions, we support McWilliams and Siegel (2001) 's assertion that CSR is the ability of a business corporation to go beyond legal and ethical compliance by engaging in business practices that seem to encourage some social good, above the interest of the corporation and that which is stipulated by law. The major aim of this paper was to offer practical solutions to the challenges facing natural gas development and exploitation in Nigeria. Data collected from five oil producing communities (Obagi, Obelle, Omoku, Ogbogu, and Obite) in Niger Delta between 2010 and 2013 were analyzed. The adoption of critical ethnography research method allowed these authors to objectively present their findings. This study concludes that only management practices, which support open and continuous dialogue with all the stakeholders and corporate socioeconomic policies that favour socio-cultural, environmental and economic concerns of all stakeholders will reap the full benefits of the Nigerian emerging economy.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.110
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.126
GPT teacher head0.315
Teacher spread0.189 · 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
Published2015
Admission routes1
Has abstractyes

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