Bibliographic record
Abstract
Purpose The purpose of this paper is to compare theoretical conceptions that reclaim and re‐think material practice – “the thing” in the social and personal mix – specifically in terms of work activity and what is construed to be learning in that activity. Design/methodology/approach The paper is theory‐based. Three perspectives have been selected for discussion: cultural‐historical activity theory (CHAT), actor‐network theory (ANT), and complexity theory. A comparative approach is used to examine these three conceptual framings in the context of their uptake in learning research to explore their diverse contributions and limitations on questions of agency, power, difference, and the presence of the “thing”. Findings The three perspectives bear some similarities in their conceptualization of knowledge and capabilities as emerging – simultaneously with identities, policies, practices and environment – in webs of interconnections between heterogeneous things, human and nonhuman. Yet each illuminates very different facets of the sociomaterial in work‐learning that can afford important understandings: about how subjectivities are produced in work, how knowledge circulates and sediments into formations of power, and how practices are configured and re‐configured. Each also signals, in different ways, what generative possibilities may exist for counter‐configurations and alternative identities in spaces and places of work. Originality/value While some dialogue has occurred among ANT and CHAT, this has not been developed to compare more broadly the metaphysics and approaches of these perspectives, along with complexity theory which is receiving growing attention in organizational research contexts. The paper purports to introduce the nature of these debates to work‐learning researchers and point to their implications for opening useful questions and methods for inquiry in workplace learning.
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.
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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.089 |
| Scholarly communication | 0.013 | 0.024 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".