A human capital perspective of skill acquisition and interface loyalty
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
There are many arts among men, the knowledge of which is acquired bit by bit by experience. For it is experience that causeth our life to move forward by the skill we acquire, while want of experience subjects us to the effects of chance. Plato To most men experience is like the stern lights of a ship, which illuminates only the track it has passed. Samuel Taylor Coleridge It has long been recognized that humans are able to improve task performance as a result of repeated experience with a particular task, and that this type of learning consistently adheres to the Power Law of Practice. However, less attention has been given to the impact that practice, and the acquisition of skill, have on a user’s loyalty to a particular software interface. Here, we review the notion of human capital, and discuss specific examples from research into online shopping, in an effort to better understand the role of learning in the development of interface loyalty. Learning by doing is an essential aspect of human knowledge acquisition. Over
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.003 |
| 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