Business responses to climate change: a case study of selected organizations in Newfoundland
Bibliographic record
Abstract
Climate change is a problem that the world is struggling to solve. Many studies and much research have been directed toward this course, but we still face its impacts. Recently, scholars have investigated the relationship between climate change and businesses. Companies have begun taking responsibility for climate change and are finding ways to combat the issue. Climate change presents risks and opportunities to businesses. Therefore, this thesis aims to appreciate business responses to climate change in Newfoundland’s natural resource sector. Using a qualitative study based on semi-structured interviews, the research examined how the selected businesses are responding to climate change. The major finding of the study was that Newfoundland lacks specific climate change regulations and requirements to drive adequate response measures from companies. It was revealed that the chosen organizations’ significant sources of greenhouse gas emissions were transportation and the use of equipment and fuel. However, most of the businesses had implemented measures to reduce their carbon footprint and addressed some climate change impacts they face. In terms of the influence of institutional pressures on business responses, this research showed that mimetic force (copying similar actions among firms) played a major role compared to the other forces. Generally, this thesis highlighted that businesses are not immune to climate change, hence companies are incorporating the impacts of climate change into their planning and are adopting actions to address the problem.
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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 | 0.001 | 0.009 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| 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 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".