INVESTASI ETIS (ETHICAL INVESTMENT) (KONSEP, DASAR PERTIMBANGAN DAN PENDEKATAN)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ethical investment has experienced very fast and high growth over the last decade. The growth and development of this investment occurs both at the local (Indonesian) level and at the global level. In Indonesia, the growth and development of ethical investment can be seen from the increasing number of ethical-based stock indices and the value of stock market capitalization in each of these indices. Meanwhile at the global level, it can be seen from the increase in the value of ethical investments, especially in the five main world markets, namely Europe, the United States, Japan, Canada and Australia and New Zealand. Underlying this phenomenon needs to be explored further on the issue of ethical investment. This article tries to explore more deeply ethical investing, especially regarding the concepts, basis for decisions and approaches (strategies) in ethical investment activities.
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.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 it