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Record W182776735 · doi:10.17877/de290r-8460

Introduction: Ironists, reformers, or rebels?

2009· article· en· W182776735 on OpenAlexaboutno aff
Priska Gisler, Silke Schicktanz

Bibliographic record

VenueTechnische Universität Dortmund Eldorado (Technische Universität Dortmund) · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican history and culture analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Public engagement has become increasingly important within the sphere of science policy making. A broad range of discursive experiments and participatory methods involving citizens, consumers, and other key stakeholders are frequently used to consult the public about their opinion of new developments in science and technology. This special issue of STI-Studies aims at addressing the role(s) of scholars in this important field. Having personally participated in a variety of public engagement exercises and public discourse experiments, and having carefully considered how we (as social scientists) fit within these exercises, we have come to realise that our roles are heterogeneous, complex and ambiguous. Social scientists complete a number of tasks in participatory science policy making: For example, they initiate public and/or stake holder discourses by adopting or even developing participatory and discursive methods. They organise and moderate various dialogues (for the case of Germany see e.g. Renn 1999). They oversee various public discourse events and evaluate the process (for the case of Switzerland see e.g. Gisler 2000-2003). They analyse and comment on the impact of participatory methods, drawing on sociological and political theories (e.g. Maasen/Merz, 2006). In brief, social scientists play a variety of formal roles, serving as organisers, moderators, evaluators, commentators and others. However, these formal descriptions are rigid and do not fully convey the underlying social, moral and political dimensions of these roles. Furthermore, there is some ambivalence between the formal functions and the socio-moral-political roles taken on by social scientists. This ambivalence arises due to a conflict between the form and content of these roles as well as the fact that multiple roles may coincide with each other. For a better understanding of the ongoing debate on participatory science policy making, it is necessary to reflect upon this ambivalence because it affects social scientists accomplishments in this important field. Our contribution to the recent debate is a kind of self-reflexive turn: We would like to carefully consider the role of the social sciences and the role(s) social scientists expect and are expected to play in the field of participatory science policy making. Therefore, in this introduction, we raise the following questions from a theoretical point of view: How do the social sciences influence participatory policy procedures? What kind of explicit and/or implicit role(s) do social scientists play in the construction of political procedures and public debates? In an effort to address these questions, we will, first, argue how participatory policy making is linked to the social sciences and its methodologies (chapter 1). Second, we will contextualize the development of participatory policy making within the methodological framework of the social sciences and the broader historical shift towards the democratization of society (chapter 2). Third, we will assess some of the roles social scientists have come to play in participatory policy making. We suggest a way of rethinking such roles by unmasking their often rather implicit social, political and moral premises and by critically reflecting on the idea that there is only a formal role played by the social sciences. This way Canadian philosopher Ian Hacking (1999). We will highlight some of the complexities and moralities linked to the concrete roles the social sciences play, especially in the sphere of science and politics. This will be discussed in more detail in the case studies and articles assembled in this issue (chapter 3). Fourth, and finally, we would like to consider some looping effects that the deconstruction of social scientific roles may have on participatory policy making on a more general level (chapter 4). The social sciences, as a collection of disciplines, could eventually contribute more to participatory policy making by reflecting on its current role(s) and by revising the methods that are applied to specific scientific fields. In doing so, the social sciences may gain considerable insight into how they function as a thought collective.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.763
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.005
Science and technology studies0.0050.002
Scholarly communication0.0000.007
Open science0.0030.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.012
GPT teacher head0.255
Teacher spread0.243 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations2
Published2009
Admission routes1
Has abstractyes

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