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Record W2111311380

Twinning as an innovative practice in public administration: An example from the Netherlands

2012· article· en· W2111311380 on OpenAlexvenueno aff
Philip Marcel Karré, Mark van Twist

Bibliographic record

Venue˜The œinnovation journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsnot available
Fundersnot available
KeywordsPublic relationsGeneral partnershipPublic sectorService (business)Service providerBusinessPolitical scienceMarketingLawFinance
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACTThe purpose of this article is to assess twinning as an innovative experiment in interagency collaboration. We do this by describing the twinning of two Dutch governmental agencies, the Immigration and Naturalisation Service (IND) and the Social Insurance Bank (SVB). We focus on the rationale behind this partnership and the activities undertaken and evaluate the twinning using two different frameworks, a means-ends approach and a multiple process model. By doing so we not only assess whether the twinning of IND and SVB can be seen as an innovative experiment in interagency collaboration but also how such practices can best be evaluated.Key words: Interagency collaboration, twinning, evaluation.Introduction: collaboration as a challengeOver the last ten years or so, judged by the vast number of academic and practical books and magazine and journal articles published on the subject, collaboration between organizations has become a key issue in both the commercial and public sector. As resources are scarce and the action autonomy of any individual actor limited at best, alliances and networks become increasingly important for the success and, ultimately, the survival of any organization.In both the public and the private sectors, organizations hope to achieve innovation and synergy by working together across their boundaries. Enterprises collaborate to develop new products, open up markets, share risks, make investments and develop knowledge (Barringer & Harrison, 2000; Doz, 1996; Reuer, 2004). Public agencies form alliances and networks to provide better services to clients with complex problems and to achieve a joint effort in tackling wicked social problems. Collaboration is also used as a tool to open up bureaucratic organizations and to let them learn from more successful ones (Bason, 2010; De Ridder, 2007; O'Leary & Blomgren Bingham, 2009; Yoshino, 1996).Collaboration is widely used as a buzzword today, but some critical work has been published (cf. Lotia & Hardy, 2008). Organizations trying to cooperate with each other often find this a challenging enterprise. The time and money cost of organizing cooperation often seem to be the main constraint in the private sector. Not surprisingly most collaboration initiatives fail in the commercial world: according to Darby (2006) up to 70% of partnerships do not deliver on their promises, a truly staggering percentage.In the public sector, collaboration often is difficult due to the fragmented nature of government as a result of the shortcomings of both traditional bureaucracy and New Public Management (NPM). Traditional bureaucracy, with its focus on functional differentiation, often impedes collaboration as it leads to departmentalism and the creation of silos or stovepipes. New Public Management practices are equally prone to hampering collaboration, as NPM's focus on performance tends to favour competition rather than cooperation (Christensen & Lae greid, 2007; Head & Alford, 2008).In order to unlock collaboration's promises and to overcome its difficulties, organizations in the public and the private sector are on the lookout for new, innovative practices which help them overcome the challenges of collaboration. We discuss one such practice in this paper, the twinning between two Dutch agencies, the Immigration and Naturalisation Service (IND1) and the Social Insurance Bank (SVB2). We describe the rationale behind this partnership and the activities to which it led and follow this by an evaluation using two different frameworks: a means-ends approach and a multiple process model. By doing so, we not only discuss whether the twinning we describe can be seen as an innovative practice but also how experimental forms of collaboration could best be assessed.MethodThis article is based on an action research project (Lewin, 1946; Argyris, Putnam & Smith, 1985; Stringer, 2007) we conducted at the behest of IND and SVB during the entire course of their twinning. …

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.030
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.039
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0240.023
Scholarly communication0.0200.013
Open science0.0030.015
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.179
GPT teacher head0.447
Teacher spread0.268 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations5
Published2012
Admission routes1
Has abstractyes

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