Bibliographic record
Abstract
Purpose This paper seeks to examine the identities and subjectivities of independent knowledge workers who contract their services to organizations. Two questions are addressed: who are these enterprising knowledge workers, in terms of how they understand and position themselves relative to organizational structures, practices and social relations in their work as “inside outsiders”? How do they recognize their own constitution, and what spaces for agency are possible? Design/methodology/approach The discussion draws upon a qualitative study of 18 self‐employed consultants in organizational change, analysing their articulations as ongoing constitutions within prescribed discourses and cultural technologies. Semi‐structured in‐depth interviews were analysed inductively to determine themes and silences among the narratives. Findings The argument shows how these subjectivities emerge from in‐between spaces, both inside and outside organizations. As they negotiate these spaces, they exercise agency by resisting control while building connections. These articulations are described as “network identities”. Originality/value The paper concludes with implications for organizations employing or contracting with such individuals. Suggestions for managers involve enabling more project structures, negotiating boundaries and purposes more clearly, providing more flexible conditions and facilitating more integration of these knowledge workers with other employees before, during and following innovative project activity.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".