The co-production spectrum: conceptual blurs in theory and practice
Bibliographic record
Abstract
Abstract Although there is an important body of work that aims to define the conceptual boundaries between co-production, co-creation, and related terms, there is often a significant mismatch between scholarly definitions and how these practices and processes are described by practitioners. Drawing upon research from Australia, England, France, Quebec, and Scotland, we analyze the narratives and discourses of co-production/ co-creation. This article highlights how practitioner terminology often diverges from more mainstream and accepted scholarly definitions of dominant “co-” concepts, with different terminology used between the five contexts to differentially focus on collaboration between organizations or between citizens and professionals, and divergence between a focus on design/ planning of services or delivery/ implementation. Simultaneously, there is convergence around arguments for engaging in these collaborative processes and norms attached to them. This article argues that focusing on the underpinning norms for collaborative engagement instead of the overt terminological labels ascribed to these processes will more productively advance public management theory. The article thus makes an important contribution to our understanding of concepts along a non-linear co-production spectrum and offers other narrative and discursive lenses through which they might be studied.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".