Bibliographic record
Abstract
Purpose The purpose of this paper is to assess the compatibility between the religious investing criteria of some Christian mutual funds and the “ Interfaith Center for Corporate Responsibility” (ICCR) shareholder resolutions about corporate unethical/illegal practices. Design/methodology/approach Among all ICCR 2007‐2008 shareholder resolutions, the paper analyze unethical practices that could lead to corporate illegalities for business corporations that are included in the portfolios of Christian mutual funds. It will determines to what extent such companies have codes of ethics that clearly explained the expected behaviour from their employees, managers, or directors about given ethical issues: sexual orientation discrimination, conflicts of interest on the board and slave labour in the supply chain. Findings About the issue of slave labour in the supply chain, managers of Christian mutual funds could not invoke ignorance since in the code of ethics of one company, there is no provision dealing with slave labour. Concerning conflicts of interest on the board, managers of Christian mutual funds could not identify potential risks related to those companies, since the problem is the applicability of their codes of ethics. Finally, companies have very different ways to address or not the issue of sexual orientation discrimination in their codes of ethics. Originality/value The originality of the paper is twofold: first to compare companies Christian mutual funds are investing in (on the basis of Christian selection criteria) and companies for which there are ICCR resolutions (the aim of such resolutions is to change some questionable or unethical aspect of a given business corporation), and second to see to what extent corporate codes of ethics are written in a way to reduce or increase the potentiality of ethical conflicts.
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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.020 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".