Post-pandemic social transformation and labor trends in sellers of repowered items in the city of Huancayo, Peru
Bibliographic record
Abstract
The COVID-19 pandemic generated significant social transformations in different sectors of society, one of the most important being the labor market. This research establishes the relationship between these transformations and employment trends among repowered item vendors in the city of Huancayo, Peru. Three key dimensions were addressed: destruction, expansion, and modification of employment. The research adopted a quantitative approach, with an exploratory, descriptive, and correlational design. Validated questionnaires were administered to a representative sample of 331 repowered item vendors. The results indicate a significant relationship between social transformation and employment trends, which is reflected in a reconfiguration of employment in this sector. A loss of job opportunities was evident; however, an expansion of employment was also observed through adaptation to new forms of marketing and the growing demand for repowered products. Likewise, changes in labor dynamics were identified, including the use of new sales strategies and the digitization of processes. In conclusion, the pandemic not only negatively affected employment in this sector, but also encouraged resilience and adaptation strategies.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".