Honour, History, and the History of Mediterranean Anthropology
Bibliographic record
Abstract
HonourThe cultural syndrome of honour and shame, as conceptually developed by anthropologists working in the Mediterranean in the third quarter of the twentieth century, came under attack in the early 1980s, when it was dismissed by Michael Herzfeld (1980: 349) as a mere 'summation of "translated" terms'.Herzfeld's critique ignited a prolonged and at times fierce debate.Some anthropologists defended the legitimacy of studying honour and, indeed, its centrality as a unifying Mediterranean value (Blok 1981, Gilmore 1987), while others, like Unni Wikan (1984) or Lila Abu-Lughod (1986), sought novel ways to address honour -and shame -largely inspired by feminist perspectives.Most participants in the debate, however, appeared to consider honour more and more as 'a red herring', to quote the title of a paper published in those years (Lever 1986).By the end of the 1980s the notion of honour was widely regarded to be not just unsuitable but positively dangerous for comparative work.Joo de Pina-Cabral's 1989 article in Current Anthropology is commonly referred to as being the last nail in the coffin of both honour and the Mediterraneanist anthropology that had been built around it.This is a well-known story, and there is no need to linger over it.There is, on the other hand, another story -a partly related and partly parallel one -which is not so well known, and yet deserves in our opinion not to be neglected.A useful starting point to introduce this story is a passage from Dionigi Albera and Mohammed Tozy's introduction to their edited book of 2005, La Mditerrane des anthropologues.As part of their plea for a more polyphonic Mediterranean anthropology, they take as an example of the asymmetrical relations between Anglophone anthropology and what might be called the 'vernacular' anthropological traditions of Mediterranean countries the contrast between the strong impact exerted by the seven-page article in Current Anthropology by Pina-Cabral (perceived as the spokesman of the autochthonous view and the gravedigger of the Anglophone anthropology of the Mediterranean centred on the study of honour) and the almost nonexistent impact of a book published in the same year in Italy which offered a very wide and articulated discussion of the theme of honour and contained contributions by John Davis and Jane and Peter Schneider as well as by researchers from different disciplines (anthropologists, historians, specialists of oral literature, sociologists) and different nationalities: Italians, French, Tunisians, Palestinians (Albera and Tozy 2005: 12).
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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 | 0.001 | 0.000 |
| 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 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.030 | 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".