THE PSYCHOLOGICAL AND ACADEMIC PRESSURES OF THE NEW CORONA PANDEMIC A SAMPLE OF STUDENTS OF THE FACULTY OF ARTS, UNIVERSITY OF MISURATA
Bibliographic record
Abstract
At the end of (2019) appeared in Yukon, the capital of the Chinese county of Kui, what is known as the emerging corona virus - COVID - 19) prompted the entire world to describe it as a crisis, as the crisis is a turning point and a tense state of transmission, and it is a critical and dangerous situation or period and an evolutionary state in which a schizophrenia occurs The inevitable transition to another state. The Corona pandemic led to the exposure of all segments of society to an unprecedented change in a short period of time, a compulsive change in the lifestyle of societies, as the economy of many countries went through difficult conditions, and it affected all health control systems in all countries around the world, preventing movement and stopping flights, and the world became a “prisoner”. All of this has made people live in a situation of pressure and tension, and the academic year for students will be different, whether in terms of preventive measures, reducing the number of School hours, or in terms of relying on remote learning, and these changes affect one way or another on the psychological reality of students, as they have not experienced such this global crisis before. This research aims to identify psychological and academic pressures among a sample of students from the Faculty of Arts, Misurata University. Keywords: Terminological And Procedural Concepts, Psychological Pressures, Study Pressures
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".