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
We have various everyday measures for identifying the presence of consciousness, such as the capacity for verbal report and the intentional control of behavior. However, there are many contexts in which these measures are difficult (if not impossible) to apply, and even when they can be applied one might have doubts as to their validity in determining the presence/absence of consciousness. Everyday measures for identifying consciousness are particularly problematic when it comes to ‘challenging cases’—human infants, people with brain damage, nonhuman animals, and AI systems. There is a pressing need to identify measures of consciousness that can be applied to challenging cases. This paper explores one of the most promising strategies for identifying and validating such measures—the natural-kind strategy. The paper is in two broad parts. Part I introduces the natural-kind strategy, and contrasts it with other influential approaches in the field. Part II considers a number of objections to the approach, arguing that none succeeds.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it