Assessing the effect of corporate social responsibility on community development in the Niger Delta: a corporate perspective: Table 1.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The widespread adoption of corporate social responsibility (CSR) policies by oil transnational corporations in developing countries have led to calls for a concerted effort to better capture CSR effects. Unfortunately, capturing the impacts of CSR is not as straightforward as it might seem. In fact, oil companies operating in the Niger Delta continue to face the challenge of how to determine the success or failure of their CSR initiatives either in terms of its effect on community development or its impact on corporate–community relations. To address this problem, Shell Petroleum Development Company (SPDC) in 2013 launched the Shell Community Transformation and Development Index (SCOTDI). SCOTDI represents an innovative framework that integrates and adapts a number of international principles into a composite index in a manner that is responsive to local context. The framework is used to assess and rank the performance of the different Global Memorandum of Understanding (GMoU) clusters within the host communities of SPDC. This article suggests that SCOTDI allows for a systematic assessment of the effects of CSR on community development and provides incentive for positive inter-cluster competition for community development. However, the framework also suffers from some shortcomings that can reasonably be addressed. The article considers the theoretical and practical implications for efforts to assess CSR contribution to community development in developing countries.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it