Figuring the Shame of Corruption in Jordanian Sociopolitical Discourse through a Range of Creative Metaphorical Scenarios
Bibliographic record
Abstract
Using the tenets of the Cognitive Metaphor Theory (CMT) and the pragmatic approach of the Critical Metaphor Analysis (CMA), this paper investigates a variety of novel metaphoric scenarios targeting the conceptualization of the abstract concept of corruption in Jordanian sociopolitical discourse. My central argument is that by employing a range of conceptual domains to elicit a strong visceral reaction in his readership, the columnist Ahmad Hasan Al-Zu’bi connects the conceptual domain of CORRUPTION back to the equally abstract (but also deeply felt) conceptual domain of SHAME as the embedded running theme in the data under investigation. Unlike the corresponding model, which is primarily concerned with mapping elements from the source domain onto the target counterpart, these scenarios provide us with mini-narratives or storylines, shedding more light on the concept of SHAME which is crystallized through the diverse source domains utilized in the columnist’s writings. The study is based on the analysis of 19 extracts taken from the writings of a popular Jordanian columnist Ahmad Hasan Al-Zu’bi in his well-known website Sawalief.com. Two main research questions are raised in this paper: 1. What types of creative metaphoric scenarios are used to frame the abstract target concept of corruption? 2. Why are these particular creative metaphors exploited in the conceptualization of the problem of corruption? Findings of the study reveal that the creative power of these metaphoric scenarios does highlight and connect back to a powerful and emotionally resonant emotion that is important in traditional Jordanian society: SHAME.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".