Identifying Challenges in Implementing Sustainable Practices in a Developing Nation
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 South Pars Special Economic Energy Zone (SPSEEZ) is the largest petroleum zone in Iran and the second biggest gas producer in the world. It is now one of the world’s most important eco-industrial poles. Despite the rapid development and activists’ calls to sustainable path, there is little systematic effort in the assessment of industrial zones sustainability in developing countries. Iran, a nation that has ratified the Rio Declaration pact, has moved forward in order to achieve sustainable development. There have always been controversial debates due to its success. This paper employs survey, interview as well as observation to explore the perception of people on planning and sustainable development efforts and to identify the most important challenges at SPSEEZ. The result shows that the major impediment against sustainability is the lack of involvement from urban planners and the public during decision-making process. Finally, the paper contributes to the identification of the most urgent problems in SPSEEZ and the functions of different stakeholders as a reference for better sustainable development planning.
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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