Using Grounded Theory to Explore Learners' Perspectives of Workplace 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
Grounded theory is an inductive enquiry that explains social processes in complex real-world contexts. Research methods are cumulative cyclic processes, not sequential processes. Researchers remain theoretically sensitive and approach data with no preconceived hypotheses or theoretical frameworks. Literature is reviewed as lines of enquiry and substantive theories emerge. Interviewers ask broad open questions, check understanding and prompt further description. Participants choose how they share their perspectives and experiences. Everything is considered data. Data is analyzed in cyclic processes. Initially coding uses participants' words, and then identifies patterns, social processes and emerging substantive theories. Memos and diagrams facilitate understanding of data and literature. Grounded theory is a suitable research methodology for work-integrated learning because grounded theory explains social processes, such as learning, in complex real-world contexts, such as workplaces, where multiple influencing factors occur simultaneously. A case study illustrates how grounded theory was used to explain learning in the workplace.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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