What is modelled during observational learning?
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
In this article, we examine the question of what information is processed during observational learning by evaluating a variety of methods, theories, and empirical data. Initially, we review work involving neuroimaging techniques and infant imitation. We then evaluate data from behavioural experiments involving adults, wherein a variety of attempts have been made to isolate the critical or minimal information constraining the acquisition of coordination. This body of research has included comparisons between video and point-light displays, manipulations to the amount and type of information presented in the display, the collection of point-of-gaze data, and manipulations to the task context in terms of outcome goals. We conclude that observational learning is governed by specific features of the model's action (i.e. motions of the end effector) and the task (i.e. outcome constraints) and, in contrast with traditional theoretical modelling, more global aspects of a model (i.e. the relative motions within and between joints) do not appear to be the primary method for constraining action execution.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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