Intermediation in intermediation: triple helix innovation and intermediary legal organisation
Bibliographic record
Abstract
Triple helix collaborations are evidence and example of larger ‘post-postmodern’ trends that have accelerated the convergence of once clearly established organisational dichotomies, in particular, market/hierarchy, private/public and for-profit/non-profit. The multiplex hybridity of triple helix collaborations creates unique challenges for the functional and, in particular, advance legal organisation and governance of their social welfare-oriented, quasi-entrepreneurial, quasi-regulatory innovation interactivity. Social innovation, resource valorisation and sustainability—constituting core normative underpinnings and objectives for triple helix models—similarly affect the design and efficiency of hybrid firms that functionally and legally domicile triple helix intermediation. In an effort to help promote the emergence of sui-generis best practices in the intermediation of ‘innovation in innovation’ (Etzkowitz, Stud Sci 42(3):293–337, 2003a) triple helix projects, this article focuses on two interrelated aspects of triple helix hybridity which are less developed in the current literatures: First, based on a well-documented case study of a failed research group-firm hybrid within the University of Helsinki, it examines an institutionalised supra-helical, fourth-party intermediation model for triple helix networks and distinguishes such theoretical model from mere inter-helical self-intermediation in trilateral university-industry-government collaborations. Second, it hypothesises the possible association of supra-helical, fourth-party triple helix intermediation in application with blended private/public, for-profit/non-profit legal entities, in particular, only recently introduced hybrid legal organisations in the UK, the USA, and Canada. The main thesis developed under such dual focus is that the unique legal organisational design and domicile for triple helix intermediation, i.e. what this article terms the supra-helical mode 3 substructure , critically matters—both, for purposes of institutionalising efficient decision-making and governance equilibria in the promotion and operation of real-world triple helix projects and for controlling the agency and social costs of such advanced triple helix collaborations.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.041 |
| Scholarly communication | 0.014 | 0.025 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".