Identification and Prioritization of the Factors Impacting the Social Responsibility of the Extractive Oil and Gas Industries
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
Destruction of Ozone layer, increase of earth temperature and climate changes as a result of GHG (Green -House Gasses) are the most significant concerns of the society these days.Since the gas and oil extractive industries can pollute the environment and there are many oil and gas installation near the residential areas, the expectations have to be attended and the local society should consider the limitations as the most challenging issues. This project has been done from Feb 2014 to June 2014 through questionnaires containing 49 effective factors based on the rules of ISO 26000 standards that have been distributed among top and middle managers. Finally the hypotheses have been evaluated by Pearson test based on the presence of a significant relationship between each of 7 variables and the social responsibility of the considered company and then the variables and their structural performances have been ordered by using Friedman test.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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