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Record W2339462849

A Design Thinking Approach to Sustainable Inclusive Shopping Environments for Grocery Shoppers with Low Vision

2015· other· en· W2339462849 on OpenAlexaboutno aff

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2015
Typeother
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsProduct (mathematics)BusinessInclusion (mineral)Citizen journalismGrocery shoppingMarketingUniversal designSustainable livingSustainabilityComputer scienceWorld Wide WebPsychology
DOInot available

Abstract

fetched live from OpenAlex

The seemingly simple daily life activity of grocery shopping could be an exhausting ordeal for people who are blind or have low vision. The objectives of this inclusive design research study were to ethnographically identify the barriers experienced by shoppers with low vision and to carry out participatory design of an inclusive solution to mitigate the situation. This report documents the four phases of the study – Discover; Define; Develop; and Disseminate. A demo prototype ‘Shopping Buddy,’ with the innovative idea of Universal Product Inclusive Code (UPiC) at its core, was designed to aid shoppers with low vision. The UPiC system will provide necessary product information to the shopper by leveraging existing data from the manufacturers’ databases. Thus, the proposed solution is not just an assistive tool; it also includes ingredients for effecting systemic changes in the retail grocery ecosystem comprising the industry’s Manufacturers, Distributors, Retailers and Consumers (MDRC). To make the benefits, and resulting inclusion, sustainable, recommendations regarding the UPiC are made to the MDRC, also addressing the needs of commercial viability. Such sustainable inclusive design will ultimately result in curb cut advantages for all shoppers, thereby enhancing sales and benefitting the Canadian economy.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.833
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0050.002
Scholarly communication0.0000.001
Open science0.0050.002
Research integrity0.0010.001
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 head0.039
GPT teacher head0.308
Teacher spread0.269 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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