An International Comparative Research on Liabilities Recognization and Provision of Asset Retirement Obligations for Extractive Industry Enterprises
Why this work is in the frame
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Bibliographic record
Abstract
This paper samples listed companies of coal,metal mining and oil and gas industries in UK and Australia and classifies as IASB group,does U.S and Canada as FASB group and China as China group,then compares the differences of recognition and measurement liabilities of asset retirement obligations(ARO) within IASB,FASB and China sample by industries.Except that companies of oil and gas industry are geared to international counterparts,enterprises of coal and metal mining industry lack of recognition ARO liabilities seriously and underestimate provision for ARO.The results show that the problems of ARO-related accounting standards,insufficient strength of investor protection and environmental regulation in China restrict the recognition of ARO liabilities and ones of environmental regulation further impacts on provision for ARO.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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