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
To clarify the role of labels in early induction, we compared 16-month-old infants' (n=114) generalization of target properties to test objects when objects were introduced by the experimenter in one of the following ways: (a) with a general attentional phrase, (b) highlighted with a flashlight and a general attentional phrase, (c) via a recorded voice that labeled the objects using a naming phrase, (d) with a label consisting of a count noun embedded within a naming phrase, (e) with a label consisting of a single word that was not marked as belonging to a particular grammatical form class, and (f) with a label consisting of an adjective. Infants relied on object labels to guide their inductive inferences only when the labels were presented referentially, embedded within an intentional naming phrase, and marked as count nouns. These results suggest that infants do not view labels as attributes of objects; rather, infants understand that count-noun labels are intentional markers denoting category membership.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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