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Record W3156491964 · doi:10.22215/etd/2019-13698

The Perception of Design: a study of the understanding of design contribution within the business management sector through comparative analysis

2019· dissertation· en· W3156491964 on OpenAlexaff
Jennifer Heaney

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsCarleton University
Fundersnot available
KeywordsInterdependenceExploratory researchKnowledge managementPerceptionProcurementDesign managementProcess (computing)Design processEngineering design processDesign scienceResearch designComputer scienceOrder (exchange)Process managementEngineeringBusinessPsychologyMarketingSociologyInformation managementWork in process

Abstract

fetched live from OpenAlex

The professions of business and design are based in distinct modes of knowledge and process but are interdependent in practice.The capacity of the designer to innovate can be negatively impacted if his/her understanding for design contribution is misaligned with that of the business manager.In order to address the way in which design is perceived by those who procure design services, there is a need to first illustrate the ways in which their perception deviates from that of the designer.This paper presents research into design understanding as a comparison between design professionals and business managers.Data for the study is obtained using both ethnographic and design research methods.Results demonstrate issues associated with understanding the complex nature of design activity through a quantitative, linear approach versus an iterative, exploratory process.

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)0.018
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0050.014
Scholarly communication0.0070.009
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.105
GPT teacher head0.335
Teacher spread0.230 · 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 designQualitative
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
Published2019
Admission routes1
Has abstractyes

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