Adoption of IFRS for SMEs in Albania
Bibliographic record
Abstract
Small Medium-Sized Enterprises (SMEs) is one of the most important engines of economic growth in Albania. They make a significant contribution to local and global trade and also to the national economic development. SMEs have the largest proportion of total Albanian employment, almost 78% of the total number of employed people. They generally face difficulties in financing and investing decisions, globalization, and other matters, mainly because of their inappropriate formal financial reports. These enterprises must prepare adequate financial statements and proper accounts to deal with third parties’ needs and ensure stakeholder’s confidence. This requires financial statements to be prepared by international financial reporting standards (IFRS), national accounting standards, and local government laws. Therefore, the International Accounting Standards Board (IASB) provided a new standard to ensure the required financial reporting quality for SMEs. The main focus of this study is to examine the attitudes of financial statement’s information’ users in Albania towards the adoption of this financial reporting standard for SMEs as progress on the general financial reporting process in Albania, and also to estimate their capabilities and interests on this matter.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".