Learning about workplace learning and expertise from Jack
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
Purpose The purpose of this paper is to highlight some methodological problems concerning the neglect of participants' voices by workplace ethnographers and neglect of the highly interactional and co‐constructive nature of research interviewing. The study aims to use discourse analysis, to show the phenomena of workplace learning and expertise to be constituted in participants' talk. Design/methodology/approach From excerpts of natural talk and research interviews by fish culturists speaking about their learning in a salmon hatchery, discourse analysis is used to analyze how workplace learning and expertise are rhetorically performed. Findings The paper finds that fish culturists drew on two discursive repertoires/resources – school‐ and workplace‐based learning – to account for their learning and expertise. The main participant affirmed the primacy of interest and practical workplace experience in his job just as he presupposed a weak correlation between school‐based (theoretical) and workplace (practical) knowing. However, both kinds of learning were deemed important though articulating this view depended on the social contexts of its production. Research limitations/implications Discourse analysis does not establish immutable truths about workplace learning and expertise but rather it is used to understand how these are made accountable through talk in real‐time, that is, how the phenomenon is “done” by participants. Practical implications There is increased sensitivity when using ethnographic and interview methods. No method can avoid being theory‐laden in its conduct and reporting but discourse analysis perhaps does it better than its alternatives. Originality/value While some contributors to this journal have also approached workplace learning from a discursive perspective, this paper attempts to understand the phenomenon solely from participants' categories and interpretations.
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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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