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 paper examines the phenomenon of ‘interactive kinds’ first identified by Ian Hacking. An interactive kind is one that is created or significantly modified once a concept of it has been formulated and acted upon in certain ways. Interactive kinds may also ‘loop back’ to influence our concepts and classifications. According to Hacking, interactive kinds are found exclusively in the human domain. After providing a general account of interactive kinds and outlining their philosophical significance, I argue that they are not confined to the human realm, but that they can also occur elsewhere. Hence, I conclude by arguing that interactive kinds pose a challenge to scientific realism about kinds by making it difficult to make a distinction between real and non-real kinds. 1. Introduction 2. The Looping Effect 3. A General Account of Interactive Kinds 4. Are All Interactive Kinds Human Kinds? 5. Awareness and Intentional Action 6. Ontology 7. Conclusion
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 | 0.001 | 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 | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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