Are Gender and Business Types Able to Withstand the Decline in MSE Turnover in the COVID-19 Pandemic Era?
Bibliographic record
Abstract
The Covid-19 pandemic that started in Wuhan, China at the end of December 2019, has had economic and social impacts globally. Indonesia did not escape the impact of the pandemic. The Indonesian economy experienced contraction in a row in the second quarter of 2020 by -5.32 and the third quarter of 2020 by -3.49 percent (BPS, 2020). This contraction was the first economic contraction since 1999, and occurred in almost all business fields including Micro and Small Enterprises (MSEs). Around 83 percent of MSMEs in the Greater Jakarta experienced the negative impact of this pandemic, and nearly 96 percent of them experienced a decrease in turnover. This study aims to analyze the factors that are holding back the decline in business turnover caused by the Covid -19 Pandemic. For this purpose, a number of variables that are thought to have an effect are tested, namely the gender of the entrepreneur, the type of business, the length of business, and the location of the business (DKI Jakarta and outside DKI Jakarta). To achieve this research objective, the survey was conducted in three administrative areas, namely the City of East Jakarta, Pesawaran District, and Palembang City. The statistical analysis used is Ordinary Least Square. The results of the analysis show that male entrepreneurs have a greater tendency to decline in turnover, the type of trade and service business has a smaller decrease, while the length of business and location of the business do not have a statistical effect.
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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 | 0.001 | 0.016 |
| 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".