Extractive Sector Stakeholders' Perspectives of the Extractive Sector Transparency Measures Act (<scp>ESTMA)</scp><sup>*</sup>
Bibliographic record
Abstract
ABSTRACT This commentary considers stakeholder perspectives of Canada's Extractive Sector Transparency Measures Act (ESTMA). In 2015, ESTMA was enacted under Canada's corporate social responsibility (CSR) strategy as a mandatory CSR reporting initiative requiring the financial disclosure of all payments relating to the commercial development of oil, gas, or minerals around the globe. Despite ESTMA's intended purpose to improve transparency and deter corruption within the global extractive sector, little remains known about the acceptance of this mandatory CSR initiative by extractive sector stakeholders. Success of this government initiative likely hinges upon stakeholder acceptance of ESTMA. This study reports the results of a survey of industry stakeholders, including managers, practitioners, and academics, on whether ESTMA positively or negatively affects transparency, financial performance, reputation, decision making, and the ability of firms to do business abroad. Findings indicate stakeholders in Canada believe ESTMA has improved transparency and has had a positive effect on the reputation of Canadian firms in the extractive sector with minimal costs to financial performance, changes to decision making, or effect on ability to conduct business abroad. Using a Canadian context, the findings provide important insights for regulators and practitioners, among other stakeholders, to better understand the effects of mandatory CSR initiatives, as well as the use of legislated financial disclosures as a CSR mechanism.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 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".