Bibliographic record
Abstract
This presentation aims to explore the ubiquity of rationality in how people make choices. Historically, rationality has been conceived of as a scheme of certain values and beliefs, most often those that are compatible with a 'scientific way of thinking'. Subsequently, those who hold a different set of beliefs and values are deemed 'irrational' or considered irreconcilably dissimilar from those who are 'rational.' What typical follows for the 'irrational' are unfavorable labels such as 'dogmatic', 'primitive', or even 'insane'. This presentation rejects these common views and offers an alternate model of rationality that depicts rationality as a template rather than a scheme of values. Rather than emphasize certain values as 'rational', this model emphasizes the role of value itself as the cornerstone of rationality. An advantage of this model is that the both the commonly considered 'rational' and 'irrational' are seen to be employing the same underlying structure in making choices; the divergence is in the values themselves and not the way of thinking. What underlies these arguments is an aim to show that human beings are more alike than different, no matter what kind of choices they make
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.019 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".