MétaCan
Menu
Back to cohort
Record W4385495001 · doi:10.3990/1.9789036557788

Constructive controversies : Redesigning democratic debate and ethical deliberation in the smart city

2023· dissertation· en· W4385495001 on OpenAlexfundno aff
Anouk Jacoba Petronella Geenen

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicSmart Cities and Technologies
Canadian institutionsnot available
FundersNederlandse Organisatie voor Wetenschappelijk OnderzoekCanadian Institute of Steel Construction
KeywordsDeliberationConstructiveDemocracyPolitical scienceEngineering ethicsEnvironmental ethicsSociologyPublic administrationEpistemologyEngineeringComputer sciencePhilosophyLawPoliticsProcess (computing)

Abstract

fetched live from OpenAlex

1. Understanding socio-technical controversies as a resource rather than a burden enhances the democratic debate on smart cities. (This thesis)2. The constructive use of socio-technical controversies by making value conflicts explicit and experiential through design, addresses the urgent need to re-enter public values into the democratic processes that surround emerging technologies.(This thesis)3. Without friction no shine: The anticipation and application of Future Frictions shines light on value conflicts in the smart city.(This thesis) 4. To strengthen its role in transdisciplinary collaboration, design needs to further develop its roles as mediator and provocateur in multi-stakeholder settings.(This thesis) 5. To restore the disconnect between economic value and public value in efficiency-driven smart city visions, we must harmonize quantitative and qualitative experiences of the city.6. To realign the academic system with the evolution of (transdisciplinary) research practices, there must be room to recognize different types of academic success.7. Grappling with complexity is a challenge apparent in many fields of inquiry, ranging from theoretical physics to design research.No matter the means of inquiry, the race to address ever-increasing complexity is always run with a lap behind.8. The list of learnings from a PhD journey is long, and those presented in the thesis barely comprise half of them.9. PhD journeys are best captured by 'Geit t neet den boktj 't waal'.10. Life is colored by the chaos of trouble.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.234
Teacher spread0.220 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicSmart Cities and TechnologiesFrench-language works237,207