Bibliographic record
Abstract
The title of this paper is highly individualistic: It uses “I” and it is very competitive! Yet I was raised in Greece when it was a collectivist culture, as is clear from Triandis (1972). I started as an allocentric and ended up as idiocentric person. In January 1948, at age 21, I came to Canada, to study at McGill University, because the Technical University (Polytechnion) where I was studying in Athens was not in good shape just after the war (e.g., poor labs). I found the contrast between Athens and Montreal as great in temperature (leaving in 50 degree weather and finding -10 F) as well as in social relationships. Montreal had an individualist culture, with people having many, but relatively superficial relationships, and that contrasted with Athens collectivism where one had few but deep relationships. In Montreal my friends talked to their parents once a month, while if I could have afforded it I would have talked to my parents every day. In Montreal social relations were fluid and quick-changing, in Athens they were stable and more or less unchanged. Traces of allocentrism remain, so that when I go back to Athens, each year, I spend time with my old friends, even 50 years after leaving. The contrast between Canada and Greece started me thinking about cultural comparisons.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".