Unemployment Concern Among University Students قلق البطالة لدى طلبة الجامعة
Bibliographic record
Abstract
For more than a quarter of a century, unemployment has become a structural problem at the global level. Despite recovery and economic growth, it has been increasing year after year. In developing countries, unemployment worsens overall as development efforts continue to fail, foreign debt is increased and rigid fiscal discipline programs are implemented. What is more dangerous is that there is a severe poverty in the current economic thinking to understand the problem of unemployment and ways to get out of it, which has encouraged the emergence of concern about unemployment. The current research aims to identify: 1. Unemployment concern among university students. 2. Statistical differences in the unemployment anxiety of university students according to the sex variables (male - female) specialization (scientific - human) grade (second - fourth). The research was determined by students of the University of Babylon and for grades (second-fourth) for the academic year (2017 - 2018). To achieve the objectives of the research, the researcher relied on the following: Building a measure of unemployment concern among university students. After reviewing the literature and previous studies related to the subject and adopting it from the point of view of the humanists, the standard was finalized after completing the conditions of honesty, consistency and ability to distinguish from (32) paragraphs divided into (4) Feilds The economic dimension, the professional dimension, the psychological dimension. In order to achieve these objectives, the researcher applied the criteria to a sample of (532) students at the University of Babylon for the academic year (2017-2018). The data were then analyzed using the statistical package for Social Sciences (SPSS) and Microsoft Excel. 1. University students suffer from unemployment concerns. 2 - There are no statistically significant differences in the degree of unemployment concern among university students according to gender variables (male - female), specialization (scientific - human) and grade (second - fourth). Based on these results, the research produced a number of recommendations and proposals. أصبحت البطالة ومنذ ما يزيد عن ربع قرن مشكلة هيكلية على المستوى العالمي، فبالرغم من تحقّق الانتعاش والنمو الاقتصادي، فنسبها تزداد سنة بعد أخرى. وفي البلاد النامية تتفاقم البطالة بشكل عام مع استمرار فشل جهود التنمية وزيادة الديون الخارجية وتطبيق برامج صارمة للانضباط المالي. وما زاد من خطورة الأمر، أن هناك فقراً شديداً في الفكر الاقتصادي الراهن لفهم مشكلة البطالة وسبل الخروج منها، وهذا الأمر الذي شجع ظهور القلق من البطالة. ويستهدف البحث الحالي التعرف إلى: 1.قلق البطالة لدى طلبة الجامعة. 2.الفروق ذات الدلالة الاحصائية في قلق البطالة لدى طلبة الجامعة على وفق متغيري الجنس (ذكور - إناث) التخصص (علمي – أنساني) الصف (ثاني – رابع). وقد تحدد البحث بطلبة جامعة بابل وللصفوف (ثاني– رابع) للعام الدراسي (2017– 2018). ولتحقيق أهداف البحث اعتمد الباحث على الآتي: بناء مقياس لقلق البطالة لدى طلبة الجامعة؛ بعد الاطلاع على الأدبيات والدراسات السابقة المتعلقة بالموضوع وتبنيه وجهة نظر الانسانيين، تألف المقياس في صيغته النهائية بعد استكمال شروط الصدق والثبات والقدرة على التمييز من (32) فقرة توزعت على (4) مجالات هي: البعد الاجتماع، البعد الاقتصادي، البعد المهني، البعد النفسي. ولتحقيق تلك الأهداف قام الباحث بتطبيق المقاييس على عينة قوامها (532) طالب وطالبة في جامعة بابل للعام الدراسي (2017-2018) ثم حُللت البيانات بالاستعانة بالحقيبة الإحصائية للعلوم الاجتماعية (SPSS) و (Microsoft Excel), وقد اظهرت النتائج بـ: 1- يعاني طلبة الجامعة من قلق البطالة. 2- لا توجد فروق ذات دلالة إحصائية في درجات قلق البطالة لدى طلبة الجامعة تبعاً لمتغيرات الجنس (ذكور - أناث) والتخصص (علمي - انساني) والصف (ثاني - رابع). وبناءً على هذه النتائج، خرج البحث بجملة من التوصيات والمقترحات.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".