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Design for Social Innovation in Canada

2016· book· en· W2617332571 on OpenAlexaboutno aff
Lorenzo Imbesi

Bibliographic record

VenueCommon Ground Research Networks eBooks · 2016
Typebook
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsnot available
Fundersnot available
KeywordsSocial innovationPolitical scienceSociologyPublic relations

Abstract

fetched live from OpenAlex

<p>Design has always played a role in the process of production, transformations in society and the economy, shifts in technology and impacts on the environment. The nature of the changes created by our post-industrial era is challenging the character of design and its role in society. The post-industrial era is creating complex projects for technology, service, systems, strategy and products. Clients are even becoming undefined stakeholders, and this can be extended to the entire community and the environment.</p><p> The rise of digital technology and the knowledge society are introducing a new culture, which can be open, participatory, shared and collaborative. Here the designer is acting as a researcher, always questioning the character of the project, its outcomes and process. Open access, co-design, crowdfunding, digital manufacturing, open-source, DIY, enabling systems and networking can be included in the toolbox of the designer and can create opportunities to drive the change towards sustainability, equity and democracy. Social innovation is leveraging forms of collaboration and co-production in which designers, innovators, users and communities co-create knowledge and solutions for a wide range of social needs, exploiting the networking technologies.</p><p> This book explores a number of areas where design can contribute to face the contemporary transformations in our society with real-life collaborative research and innovation projects. Through a number of Canadian social innovation case studies collected in social, environmental and technological fields, we recognize how the role of the designer cannot be limited to the production of finished objects; rather, designers can create tools and platforms to help users and citizens participate in projects, even allowing forms of personalization.</p>

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.268
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.153
GPT teacher head0.322
Teacher spread0.168 · 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 designTheoretical or conceptual
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

Citations3
Published2016
Admission routes1
Has abstractyes

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