Love, Friendship, and Disaffection in Plato and Aristotle: Toward a Pragmatist Analysis of Interpersonal Relationships
Bibliographic record
Abstract
Although much overlooked by social scientists, a considerable amount of the classical Greek literature (circa700-300BCE) revolves around human relationships and, in particular, the matters of friendship, love and disaffection. Providing some of the earliest sustained literature on people's relations with others, the poets Homer (circa 700BCE) and Hesiod (circa 700BCE) not only seem to have stimulated interest in these matters, but also have provided some more implicit, contextual reference points for people embarked on the comparative analysis of human relations. Still, some other Greek authors, most notably including Plato and Aristotle, addressed these topics in explicitly descriptive and pointedly analytical terms. Plato and Aristotle clearly were not of one mind in the ways they approached, or attempted to explain, human relations. Nevertheless, contemporary social scientists may benefit considerably from closer examinations of these sources. Thus, while acknowledging some structuralist theories of attraction (e.g., that similars or opposites attract), the material considered here focus more directly on the problematic, deliberative, enacted, and uneven features of human association. In these respects, Plato and Aristotle may be seen not only to lay the foundations for a pragmatist study of friendship, love, and disaffection, but also to provide some exceptionally valuable materials with which to examine affective relations in more generic, transhistorical terms.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.037 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".