The Common Good: Choosing Alternative Values, Narratives and Consciousness
Bibliographic record
Abstract
The notion of the common good has never been more necessary or more problematic. It is necessary as a means to resist current unjust eco-social and economic patterns at the heart of neo-liberal globalized capitalism or, as I tend to refer to it, corporate-led globalization. One such pattern is privatization which, as I argue later in this paper, tends to exclude those who face economic barriers to full access to basic services such as education and health care. On the other hand, the concept of the common good is problematic in a postmodern world where people are quite aware of cultural pluralism and historical particularity. Is a value, that is recognized as satisfying human needs and desires, always culturally relative, or do some values cut across cultures by addressing basic human needs and fundamental human desires? What are the elements of a good society, and is it even possible to identify these elements without engaging in an oppressive type of universalism? Is there such a thing as a proper relationship between individuals and their local, regional or global communities? If so, is it possible to outline this relationship while still respecting and valuing individual and cultural diversity?
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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 | 0.023 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.013 | 0.092 |
| Scholarly communication | 0.031 | 0.036 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".