Assessing the Sustainability of Technological Developments: An Alternative Approach of Selecting Indicators in the Case of Offshore Operations
Bibliographic record
Abstract
In general, ‘sustainability’ implies accountability for effects on the natural environment and to future generations. This accountability should be extended at least to the whole Earth (in space) and several generations (in time). If this criterion is implied, most of the widely accepted technological developments are not sustainable. Moreover, conventional evaluation methods of sustainability using inappropriate indicators usually misrepresent unsustainable technologies as ‘sustainable’. In this study we developed a framework for analyzing indicators of sustainable technological developments. Problems and misconceptions about conventional indicators/indices selection were identified and discussion was carried out about how they mislead in measuring the real progress in environmental and socio-economic developments. Following the proposed framework, a set of indicators were analyzed and selected in the case of offshore hydrocarbon operations. To select these indicators, the ‘multi-criteria analysis’ method was used and was found advantageous when applied in a complex and stochastic system, such as the marine environment. The selected set of indicators were evaluated in terms of their degree of importance by simply ranking each indicator, following a modified semantic and finally appropriate indicators were sorted out based on the cognitive mapping analyses. This indicator selection process helps us discard misleading indicators and selecting appropriate sustainability indicators. Correct indicators will be useful to evaluate status of sustainability and will lead to achieve the overall objective of sustainable developments.
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How this classification was reachedexpand
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 | 0.013 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".