Green Entrepreneurship & Corporate Social Responsibility: Comparative and Correlative Performance Analysis
Bibliographic record
Abstract
In investment and trading, different CSR/CSE (Corporate Social Responsibility/Corporate Social Entrepreneurship) moral ethical firms, categorized in a number of groups, may be suitable for different financial instruments (i.e. USA sector ETFs) and different market volatility situations. For the purpose of this article we first (i) analyze the trading return performance of four CSR/CSE categories (in particular: green building, green products, green services, and green transportation); and then (ii) examine and comment the correlation between the market performance of a number of firms belonging in these four CSR/CSE categories and historical ETF market volatility. Finally, we (iii) suggest CSR firms as trading tools according to dominant market volatility. Other CSR/CSE categories (like: sustainability, executive sustainability, renewable energy, green IT, green ICT, etc.) would be examined in future research by following the introduced by this paper approach. Paper concludes that, in relatively less volatile markets the Green Transportation CSR/CSE ethical firms display better results. On the other hand, in strong market volatile situations it is better to trade Green Products CSR/CSE and Green Services CSR/CSE ethical firms. Finally, the Green Building CSR/CSE ethical firms are uncorrelated with the market volatility, as well as their performance is poor in all market cases.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".