Tidying the territory: questioning terms and purposes in work‐learning research
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 argue that foundational terms in work‐learning research, specifically “learning”, “work”, and “workplace”, are inherently complex and contested as the same as their scope has expanded in different fields to elide various conceptual categories and theoretical positions. Yet researchers often use these terms without explanation, or as generic abstractions. The article suggests rigorous questioning and more precise delineation to reveal conceptual tangles in work‐learning research and build links across disciplinary languages and research traditions. Design/methodology/approach The argument is theory‐driven, and draws upon a meta‐review of work‐learning studies published in ten journals in the period 1999‐2004. Findings Often without clarification, the term “learning” in work is used to refer to learning as “product” (knowledge acquisition, transfer, control), as “process” (as cultural change, individual development, network dynamics, practice, collective sense‐making, identity negotiations, or problem‐solving), and as all conscious human experience. Work is used to refer to almost any activity, paid and unpaid. Issues of power relations in work become side‐stepped with these conflations, and the conceptual categories dissolve when they cannot distinguish what is not learning. These issues blur the contribution of work‐learning research (e.g. what is gained through learning studies focused on one context defined by labor relations). Practical implications More precise definitions of terms, conceptualizations and purposes in work‐learning research may help reveal conflicting positions, absences, similarities and links, towards more dialogue and rigorous theory‐building across fields. Originality/value The article intends to help researchers pause and reflect on the fundamental concepts and processes they seek to explore.
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 | 0.015 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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