Hybrid organizations: A Systematic Review of the Current Literature
Bibliographic record
Abstract
The purpose of this paper is to systematically review literature concerning hybrid structures, that is, structures that are used to implement various forms of management. More specifically, the authors aim to answer two questions: can the evolution of hybrid organizations be analyzed and mapped, and if so, what are the factors that govern their development? The document is based on a systematic review approach of Little et al. (2009), which aims to make the selection of literature and the review process transparent and replicable following steps, eliminating the problem of prejudice to ensure objectivity of the research and credibility in the results as demonstrated by Rosenthal (1979) and Cooper (2003). What emerges from the literature of hybrid organizations seen from the point of view of NPM, the concept of Paradox, PPPs and Hybrid Impact is very interesting because by tidying up the concepts that various scholars have found it is possible to define what have been the factors that influenced the evolution of hybrid organizations giving a historical definition and helping to understand the roots of the concept and specifically where these new entities will generate impact. Several documents have analyzed the contribution of these approaches to the improvement of Management, Decision-Making, Identity Work, Governance, Hybrid Laws, Microfinance Institutions MFIs and Corporatizing. Through this research the authors hope to contribute to the academic and professional community by summarizing the known literature and suggesting paths for further research precisely because it is necessary the cooperation.
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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 | 0.014 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.036 | 0.025 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".