Bibliographic record
Abstract
An OverviewThis paper reviews the global environmental performance of General Motors Corporation (GM), as publicly reported. GM has a global presence in automotive manufacturing and other non-automotive business interests. GM’s products and facilities play a contributing role in the ecological footprint due to its global market presence.GM’s environmental reporting is based on the CERES (Coalition for Environmentally Responsible Economies) principles. CERES is a coalition of environmental, investor and advocacy groups, which have a mutual interest in a sustainable future. Environmental performance elements reviewed are public accountability, plant performance, product performance and stakeholder relationships.GM’s global performance can be summarized as being above expectations in the areas of public accountability, plant performance, and stakeholder relationships. Alternatively, GM is considered to be below expectations with its product's average fuel economy performance in North America. While the model-by-model performance has improved, the overall fleet has not improved since 1994 due to a market shift from passenger cars to less fuel-efficient SUV’s and personal use trucks. Unlike competitors Toyota and Honda, GM does not have a small fuel-efficient hybrid passenger car. These hybrid products provide the ability to improve the average fuel economy rating for a manufacturer.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.247 | 0.137 |
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".