Perception of Unemployment Reasons during Coronavirus Lockdown in Ukraine
Bibliographic record
Abstract
Work has always been a domain where individuals experience distress. However, in the current pandemic and into the unforeseeable future, job loss and unemployment stress will only exponentially increase. This manuscript represents the vision in vocational psychology which aimed to find out how the perception of the reasons for job cuts of males and females shifted in the first stage of the lockdown, to check and to compare the male’s and female’s ideas about the causes of their own long-term unemployment and their ideas about possible ways out of the unemployment in the situation of a COVID lockdown in Ukraine. Methods: The research agenda includes exploring of the unemployment crisis among participants who were divided into three age groups of both gender: younger (18-25-year-old), middle (26-35-year-old), older (36-50-year-old). To characterize unemployment in the pandemic period, the questionnaire consisting of three scales was developed. It aimed to discover the reasons for job cuts, the ideas about the causes of the participants’ unemployment, and possible ways out of the unemployment situation. Student t-test was used to determine if the means of two sets of data (male and female of different age groups) are significantly different from each other. Results: It is revealed that the unemployment in Ukraine among all groups of workers showed the different perception of the reasons for job cuts; their ideas about possible ways out of the unemployment in the situation of a COVID lockdown in Ukraine, which showed the generation gap in the job cuts perception and the basics of the interaction between the employer and the employee. Conclusions: The study provides deeper insights into the labour market and its personal perception by males and females of different age groups in the first stage of a COVID lockdown. Concerning results, consider the passivity of the unemployed, their inertia and unproductive employment strategies, a decline in trust to the media as employment search, and a growing tendency to despair of the ability to find a job. On the positive side is a growing understanding of education importance.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".