Bibliographic record
Abstract
Intentionality and the MindDuring the 1980s, many philosophers of mind, and even the occasional cognitive scientist, were very exercised about something called "the problem of intentionality."The problem was something like this.There are certain things in the world that appear to possess, through their operation and functioning, a special kind of property: intentionality.This is the property of being about something, of having content about that thing, of carrying information about that thing.The problem of intentionality was threefold: to explain what intentionality was; to delineate which things had intentionality (and so which things didn't); and to provide an account of just why they had not only intentionality, but the particular intentionality they had-their content .The third of these chores was the core one, the task of specifying in virtue of what certain things in the world were about the particular things they were about.The problem of intentionality was especially pressing within the naturalistic view of the mind that motivated much of the discussion of the problem.The idea was to view naturalism as a kind of constraint on what could count as an acceptable endeavor to complete the core chore: that one's account of what made for intentionality could not itself rely on unexplicated intentional or semantic notions.An answer to the problem of intentionality must be given solely in terms of "naturalistically acceptable" notions, such as causation, counterfactual dependence, material composition, biological function, or phylogenetic history.To understand a little more about the problem of intentionality, we need to turn to its second part, the part that divides the world into things with intentionality and things without it.Two of the things that paradigmatically have intentionality are the language that people use to communicate, Meaning Making and the Mind of the Externalist
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.035 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".