The expected impact of applying IFRS (17) insurance contracts on the quality of financial reports
Bibliographic record
Abstract
This study aimed to explore the expected effect of applying the International Financial Reporting Standard (IFRS) 17 Insurance Contracts on the quality of financial reports. The study followed the exploratory descriptive analytical approaches. A questionnaire was developed and distributed to a sample of 120 financial employees in all insurance companies in Jordan. It concluded that the expected impact of applying the standard on the quality of financial reports was significant, especially on the comparability of financial reports, and faithful representation. It was found that there is an expected, statistically significant and positive effect between the application of the standard, and the quality of financial reports in general, and the expected influence of applying the standard and each of comparability, faithful representation, relevance, verifiability, timely, and understandability respectively. The study recommends the application of the standard in the specified time, work to create appropriate conditions, and the need to follow objective assumptions from the company's management for the estimation of cash flows when applying the standard.
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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 | 0.002 | 0.003 |
| 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 | 0.000 | 0.000 |
| 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".