Self-assessment, Self-direction, and the Self-regulating Professional
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
One of the cornerstones of autonomy for any profession is the claim to self-regulation. To be effectively self-regulating, the profession generally depends on the individual practitioner to self-regulate his own maintenance of competence activities. This model of individual self-regulation, in turn, depends on the practitioner's ability to self-assess gaps in competence and willingness to seek out opportunities to redress these gaps when identified. The literature relevant to these processes, however, would suggest this model of individual self-regulation is overly optimistic. We review the literature and describe several difficulties associated with the traditionally held model of individual self-regulation. In particular, research demonstrates repeatedly that 1) self-assessment is not an effective mechanism to identify areas of personal weakness and that 2) even when areas of weakness are obvious to the adult learner, we often avoid engaging in learning in these areas because such learning often takes more energy and commitment than we are willing to expend. Implications of these difficulties for the current model of self-regulation are explored.
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 | 0.068 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.014 |
| 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