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Record W2735418005

It’s the little things that matter:A ready-to-assemble SMARTKIT to help people organize consumables at home by hacking furnishings through a do-it-yourself approach

2017· dissertation· en· W2735418005 on OpenAlexaff
Ding Ling

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2017
Typedissertation
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsOntario College of Art and Design
Fundersnot available
KeywordsHackerContext (archaeology)ConsumablesDemocratizationDemocracyInternet privacyEngineeringComputer scienceBusinessComputer securityMarketingPolitical sciencePolitics
DOInot available

Abstract

fetched live from OpenAlex

Democratization is broadly applied in material design and technology innovation, but little is known about democratic design in the digital context. Inspired by the practice of enchanted objects, this paper applies user-centered design as the primary research methodology to investigate what kind of democratic digital solutions might help Millennial-aged consumers streamline their home routines. SMARTKIT is a hacking toolkit created to allow individuals with little hacking ability to enchant the ordinary functionality of home furnishings and endow them with new capabilities which provide personal and social services that monitor and manage home consumables. By adding easy and affordable DIY enchantment, the democratically-designed SMARTKIT will help empower users to design the future of their homes in an accessible and affordable way that fulfills the unique requirements of each user. \nSMARTKIT makes the little things matter.

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 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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0020.005
Scholarly communication0.0050.007
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.006

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 head0.069
GPT teacher head0.323
Teacher spread0.254 · 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 designBench or experimental
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

Citations1
Published2017
Admission routes1
Has abstractyes

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