Sustainable development in an industrial enterprise: the case of Ontario Hydro
Bibliographic record
Abstract
Purpose This paper seeks to present a longitudinal case study of Ontario Hydro – an industrial organization that used sustainable development as the basis for a strategy of social and organizational transformation. Design/methodology/approach The paper describes the complex factors that influenced the formulation and implementation of this strategy. Findings The findings indicate the advanced ambition and authenticity of Ontario Hydro's strategy, even though it was formulated some ten years ago. The study suggests that the strategy was abandoned for reasons that include the gap between the processes identified in the strategy and the processes followed in practice, the absence of platforms to discuss and agree the meaning and practice of sustainable development within the company and its wider system, and the scarcity of skills to facilitate sustainable development as a process of multi‐actor innovation. Consequently, the concept of sustainable development was not translated into practices that had shared meaning for the many actors involved in the energy system of Ontario. While based on a case study of one organization, the findings appear to speak to more general issues of sustainable development as the management of organizational and contextual change. Practical implications The paper indicates much about the process of organizational change to effect more sustainable practices within a company and its social context. Originality/value No other organization has pursued a strategy for sustainable development with the same claim to authenticity as that of Ontario Hydro, where the strategy was cross‐referenced to Agenda 21 and developed with input from some of the main architects of Agenda 21. Moreover, few studies of sustainable development in the literature span a period as long as this case.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".