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Record W2114483282 · doi:10.1177/0038038508094574

`Knowledge Once Divided Can Be Hard to Put Together Again'

2008· article· en· W2114483282 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSociology · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsCarleton University
Fundersnot available
KeywordsReflexivitySociologyNormativeEpistemologyArgument (complex analysis)Field (mathematics)Embodied cognitionDivision of labourKnowledge productionSocial epistemologyKnowledge managementSocial scienceComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

This article critically examines team and collaborative research as an `academic mode of production'. Our main argument is that while theoretically qualitative social science research is rooted within a postfoundational epistemological paradigm, normative team-based research practices embody foundational principles. Team research relies on a division of labour that creates divisions and hierarchies of knowledge, particularly between researchers who gather embodied and contextual knowledge `in the field' and those who produce textual knowledge `in the office'. We argue that a theoretical commitment to a postfoundational epistemology demands that we translate this into concrete research practices that rely on concerted team-based relations rather than divisions of labour, and a reflexive research practice that strives to involve all team members in all aspects of knowledge construction processes.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.452
GPT teacher head0.559
Teacher spread0.107 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it