Begging Phenomenon in Jordan: Family Role and Causes
Bibliographic record
Abstract
The study aimed to find out the role of the family in facing begging phenomena and its causes from the point of view of Jordan Families. The study population consisted of 865339 families from Amman, the Capital of Jordan. The study sample was chosen randomly, and it consisted of 4750 families. The study used a questionnaire to collect its data. To answer the first and third questions, means and standard deviations for each item and the whole domain were calculated. To answer the second question, the means, standard deviations, t-test, and one way ANOVA Analysis were used. The study revealed that some families encourage their kids to beg and seek help from others. In addition, families are busy with other responsibilities and they do not give their kids the required support that educate them and keep them away from begging. Also, there are multiple reasons that have stood behind the wide spread of the begging phenomenon such as the current difficult situation that Jordan society experience due to economic, social, and political conditions. The study revealed that low level of education for mothers is not behind the begging phenomena, but rather it is the family income at first. Unemployment reduces family income which makes the individuals to search for other means of satisfying the family needs. This, however, finally result to begging.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 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) | 0.004 | 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".