Adult Literacy: Challenges Facing Adult Syrian Refugees With Minimal Or No Prior Formal Schooling
Bibliographic record
Abstract
The 1951 Geneva Convention relating to the Status of Refugees describes a refugee as a person who "owing to a well-founded fear of being persecuted... is unable to or, owing to such fear, is unwilling to avail himself of the protection of that country. " (UNHCR web site). Every year, millions of people around the world are forced to leave their homes to save their lives. The UN Refugee Agency (UNHCR, 2019) points out that over 80 million people are currently displaced due to different reasons, such as armed conflicts, famine, diseases, and other natural disasters. Recently, the catastrophic wars in the Middle East obliged millions of people to flee their home countries and seek refuge in safer places. The purpose of this study is to explore the reasons and the effects of limited English literacy skills from the perspectives of the two groups of the study participants (the Syrian participants and the ESL teachers) on the Syrian participants' integration and the resettlement process. This research study follows a qualitative research design by conducting semi-structured one-on-one interviews with the eight adult male Syrian participants and the four ESL teachers. The data analysis process started with open codes. Then, similar codes were grouped together to form themes and subthemes. The results indicated that all Syrian participants left their schools at an early age in Syria because they wanted to get a job to help their families. Secondly, they pointed out that their major challenge after moving to Canada was the English language which hinders their integration process. On the other hand, the ESL teachers pointed out that they need more training sessions on how to teach and deal with different refugee students coming from different parts of the world. Besides, they mentioned that the curriculum guidelines they use at their school do not meet the students' learning needs. The study concludes with recommendations for a better understanding of the urgent needs of the refugee students to help them understand the language as well as the culture of the host country.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".