Bibliographic record
Abstract
Explaining consciousness seems like an incredibly daunting task.I suspect the reason for this is because of what our explanatory theories of consciousness are expected to involve and what they are expected to look like.With the hope of deflating what is apparently required from an explanation of consciousness, I show that (i) we can shed peripheral and unproductive explanatory tasks from the enterprise of explaining consciousness, and (ii) demonstrate a means of developing much simpler explanatory theories of the phenomenon.In completing the first, I argue that our explanatory theories need not serve as interpretive tools to understand what experiences are like, and that we need not expand our scientific inquiry in search of "extra ingredients".As for the second, I motivate a semantic view of theories, wherein our explanations of consciousness may be agnostic about potential answers to other persisting philosophical problems such as the mind-body problem.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.034 |
| Scholarly communication | 0.010 | 0.029 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".