Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This thesis addresses two problems of trust: \n \n1. Knowledge on Trust: If we are provided with information by a variety of individuals, whom we trust to different degrees, what is the best overall theory we can form from the information we are given? \n \n2. Social Trust: If one does not have direct experience of an individual, how can one establish an initial degree of trust through the offices of society? \n \nIt addresses the first problem by developing a formal, mathematical and computational, model of Bonjour’s Coherence Theory of Knowledge, and the second by adapting abstract argumentation theory to reason about networks of relationships of trust and distrust between individuals. In developing the latter it develops a notion of generalised argumentation systems, giving their semantics via the Galois Connections induced by binary relations, and provides a general scheme of evaluation of these systems based on propositional model finding. \nThroughout, some effort is made to set the work in the context of both theories of trust and of the day-to-day trust situations that one encounters in everyday life.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it