Creating fragile dependencies: corporate social responsibility in Canada and Ecuador
Bibliographic record
Abstract
Discussion around the concept of Corporate Social Responsibility (CSR) re-intensified in the 1990s as a response to the increasing power of large corporations, the regulatory vacuum left by neoliberal market deregulation and the changing nature of the state in the context of globalization. This dissertation analyzes the constitution of CSR, grounded in political economy and situated in the context of globalization, and identifies CSR as a constitutive element of global governance. Claims made about the potential business contribution to social and economic development in developing regions are largely unsubstantiated and little is known about the impact of CSR on the people it is supposed to benefit. Mainstream literature strips CSR from its context and assumes that practice can be standardized and the results quantified. The qualitative case study analyzes the contextual practice and impact of CSR activities by EnCana Corporation, Canada’s largest independent oil and gas company, on Indigenous peoples and settler communities in Ecuador, and on the Dene Tha’ First Nation in Canada. Analysis of EnCana’s definition and implementation of CSR reveals a conflicting narrative, attempting to reconcile competitive capitalism with broad moralistic principles and ethics. Corporate culture prioritized the business case and the assumption that triple bottom line goals are compatible and mutually reinforcing. Findings from the case study demonstrate that corporate ideology remained constant across the company’s operations in the two countries, allowing adaptation of its CSR practices only within a certain range of possibilities. The case study provides evidence that EnCana Corporation had to adapt its CSR practice in response to specific articulations of local social-economic and political contexts. Specifically, CSR practices responded first, to national development goals and state capacity; and second, to Indigenous and communal resources and strategies. The findings further suggest that CSR practice creates fragile dependencies, subjecting social, ecological and social justice objectives to economic imperatives. Two important processes contribute to the creation of fragile dependencies. First, at the business-society interface, citizens are conceptualized as stakeholders; second, participation in decision-making becomes institutionalized as a limited form of consultation, often delegated to project proponents, without sufficient involvement of the state.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".