Performance assessment and decision-making tools for the development of eco-industrial and tertiary parks: Applications in the French and Quebecois context
Bibliographic record
Abstract
Industrial parks, commonly defined as physical spaces developed for the use of several firms simultaneously and managed by a designated manager, currently face challenge pertaining to their development and operation. Sustainable development, regarded as the conjunction of its three pillars, respectively environmental, economic and social, appears to be the answer to those challenges. This thesis is concerned with the development of a model supporting industrial park managers with their commitment to sustainable development. The presented approach is systemic and global, it seeks continuous improvement on long time horizons. The proposed model consist of a systemic modelling of the sustainable industrial park called mixed-use ecopark, a decision marking method for the establishment of an action plan and a performance expression sub-model.This model was validated with industrial parks from France and Quebec that offers a diverse panel of size, degree of maturity and commitment to sustainable development. This diversity enriched the reflection and strengthened the genericity of the developed model.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".