The Effect of COVID-19 on the Performance of SMEs in Emerging Markets in Iran, Iraq and Jordan
Bibliographic record
Abstract
This research aims to investigate the effect of COVID-19 on the performance of small and medium enterprises (SMEs) in emerging markets in Iran, Iraq and Jordan. In order to collect the required data, a standard questionnaire provided in the literature was used. The research period is the second quarter of 2022, and its population includes managers, accountants and auditors engaged in listed and non-listed companies. The research findings indicate that the outbreak of COVID-19 has affected SMEs’ performance in investigated emerging markets. For the first time, this research has examined the impact of COVID-19 on the performance of SMEs in emerging markets. The research was conducted in the three countries of Iran, Iraq and Jordan, which have different environmental conditions indicating the impact of contextual factors on the effects of the spread of COVID-19. The results can be useful for different parties, such as SMEs’ owners and regulatory bodies in similar markets.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".