The Applications of Non-financial Indicators in Business Assessment
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
The traditional one-dimension financial performance indicators has become unable to adapt to new requirements for enterprise performance evaluation because of its inherent problems such as shortsighted,lagged and other defects.A trend of the enterprise performance evaluation is to introduce non-financial evaluation indicators in the performance evaluation index system.However,non-financial performance indicators are almost at everywhere.It is not easy to select some specific indicators that closely match with the strategic development from so many indicators.In addition,many non-financial indicators are difficult to quantify,and the internal relationships among those indicators are also difficult to determine.So,compared with the applications of sophisticated system of financial performance indicators,the choice of non-financial indicators is still vague.Further,the performance indicators are the basis of the performance evaluation index system.Thus,the article is focused on basic work that trying to develop some useful setting of the non-financial indicators and evaluation.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it