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I “Like” Design: Participatory Web Sites and Design Lessons for the Masses

2013· article· en· W4409579067 on OpenAlexaff
Mary Anne Beecher

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsParticipatory designComputer scienceCitizen journalismWorld Wide WebSoftware engineeringHuman–computer interactionEngineering

Abstract

fetched live from OpenAlex

In North America, published advice literature and design-based television and radio programming served as prominent vehicles for communicating lessons about what or what not to do when making their own interior design decisions to the general public in the twentieth century. This passive approach to teaching the lessons of design has been supplemented in recent years by a more interactive model: the participatory web site. This research is a qualitative analysis of social media platforms, independent web sites and blogs that monitor and promote new contemporary works from around the world and this paper focuses on the content of four: designsponge.com, apartmenttherapy.com, clippings.com, and houzz.com. By providing platforms that use imagery and text as persuasive devices to promote new designs, such sources present the qualities of “good design” to be potentially absorbed by the general public. By linking site readers to design professionals or by addressing direct inquiries about solutions to design problems, today’s participatory sites enable non-designers to envision improvements to their own environments. The invitation to comment on designed products and spaces provides a valuable vehicle for formulating and sharing critical perspectives on the qualities of design that matter most to those who participate.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.823
Threshold uncertainty score0.275

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.199
GPT teacher head0.348
Teacher spread0.149 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2013
Admission routes1
Has abstractyes

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