A Corpus-Assisted Critical Discourse Analysis of the Syrian Refugee Crisis in Jordanian Newspapers
Why this work is in the frame
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Bibliographic record
Abstract
The present study employs corpus linguistics and critical discourse analysis to investigate the attitudes of Jordanian news towards the Syrian refugee crisis. The corpus of the research, which consists of 10140 articles (Word types: 103170 and Word tokens: 1956589), were taken from the Petra news agency between 2016 and 2018. Antconc Tools Version 3.4.4w was used to analyze the data. The study used corpus statistical tools of collocates and concordance. Collocates tool used to create a list of 200 collocates associated with the words: /lad3iʔ/ ‘refugee’, /lad3iʔi:n/ ‘refugees’, /su:ri:/ ‘Syrian’, and /su:ryi:n/ ‘Syrians’. These collocates were organized into two thematic categories: ‘services and resources’ and ‘Jordanians and Syrians’. The study used a concordance tool to unveil the attitudes of newspapers towards the Syrian refugee crisis. The findings of the study showed that Jordanians see Syrians as “brothers” and “guests”. However, Jordanian newspapers overstated the negative effect of Syrian refugees on the Jordanian economy, education, healthcare, etc. Jordanians were frustrated because Syrians compete with them on their resources and governmental services.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.118 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it