“Are Greeks Desperate for Heroes?” A Corpus-based Investigation of Colonial Discourses
Bibliographic record
Abstract
Joining previous research on the discourses that have been produced on Greece by the Western press during recent years—particularly related to the economic crisis—the present article examines the British media narratives which covered the archaeological excavation of the mound of Kasta in Amphipolis, Greece, in order to trace any possible colonial discourses. By deploying corpus linguistics in the form of word lists and concordance tables, a total of 324 articles from 108 British publications were investigated. In this study, I argue that Michael Hertzfeld’s concept of ‘crypto-colonialism’ is an ongoing situation that Greece finds itself in and has been greatly perpetuated due to Western colonial discourses that manifest themselves both explicitly and implicitly. These discourses present the ancient past as a kind of cultural example that modern Greeks should somehow follow. Consequently, a cycle of self-colonisation where colonial discourses abroad inform self-colonising discourses domestically emerges, highlighting the dynamic and complex character of crypto-colonialism and the power relationship between the West and Greece that still exists. Finally, I advocate the benefits of using corpus linguistics in cultural research, as a tool for wide-reaching empirical research.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".