Learning as Grounding and Flying: Knowledge, Skill and Transformation in Changing Work Contexts
Bibliographic record
Abstract
Before activities in workplace skill development and skill transformation can be pursued, what exactly is meant by `skill' requires careful examination. The notion of `skill' is far from consensual or accepted unproblematically, and this article is focused on the various meanings and problems that have arisen around `skill'. Four conventional conceptions of skill are examined critically and rejected: that a skill exists as a discrete competency, that a skill is `acquired' and is centered in the individual, that work skill (and knowledge) is learned through mental reflection on `concrete' experience, and that skill development is about behavior, not politics. Towards expanding conceptions of work learning, contemporary theories applicable to changing work environments are outlined: learning as participation in situated practices, as expansion of objects and ideas, as `translation' and mobilization, and as embodied emergence. Drawing insights from these four perspectives, a conception of work learning embedding a double movement of `flying' and `grounding' is offered. The argument is theory-driven and largely focused on work contexts subject to rapid knowledge transformation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.035 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".