Indicators for Sustainable Development
Bibliographic record
Abstract
Abstract In 1996 Statoil, Amoco, BP, Conoco and Shell wished to benchmark how companies in the oil business deal with the issues of the environment and sustainable development. The initial conclusion was that a methodology or process had to be developed first. It was decided that the principle focus of the process should be the management systems that each company had in place and the sharing of best practice. A four year journey of discovery began. The process included the following elements: an agreement on assessing sustainable development through a process of mutual learning an agreement based on trust and openness to enable learning definition of relevant sustainable development indicators along the value chain a description of an implementation chain for management processes measuring management processes comparing and discussing results of measurement using case studies to modify and/or verify indicator definitions used in the process. GRI, Gothenburg Research Institute acted as facilitator and was primarily responsible for the format and organisation of the many project meetings. In 1997 the process that included what we called "Environmental Management Indicators" (EMI) for the oil industry was concluded. A final report was prepared, discussed and agreed upon. However, this final report became the first phase in applying the same process to consider the sustainable development issue. This second phase was more difficult and ambiguous, compared with the environmental management indicator exercise. No ready-made standards are available with regard to the definition and measurement of Corporate Social Responsibility. Although there is some more or less theoretical literature at hand, this literature is of relatively little use when it comes to definitions and measurement of management systems that deal with sustainability issues on a company level, specifically in the oil industry. Much effort went into defining indicators, measurements and profiles for single indicators and the management systems that control sustainable development issues in the companies. The exercise resulted in a methodology and a set of indicators for assessing a company's management of sustainable development, which probably is in the forefront of the development in this area. The process has been extremely interesting and proved valuable but there is still room for improvement. The benefits of this methodology have included: learning from the sharing of best practice providing a framework for discussions with others assessing where a company's strengths and gaps are
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.029 | 0.015 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".