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Record W4251433843 · doi:10.1504/ijkbd.2017.082430

Cooperation and knowledge exchanges in creative careers: network support for fashion designers' careers

2017· article· en· W4251433843 on OpenAlexaff
Amina Yagoubi, Diane‐Gabrielle Tremblay

Bibliographic record

VenueInternational Journal of Knowledge-Based Development · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsUniversité TÉLUQUniversité du Québec à Montréal
Fundersnot available
KeywordsCreativityReputationTransition (genetics)BusinessCreative industriesKnowledge managementService (business)FordismSociologyMarketingPolitical scienceEconomyComputer scienceEconomics

Abstract

fetched live from OpenAlex

The fashion worlds describe the transition from Fordism towards a new type of economic model and supply chain in which creativity and innovation are favoured and where networks and reputation become more important for international branding. The world of fashion design is one that is characterised as being cultural and creative. It is worth considering that the transition from Fordism to a service oriented economy brings forth major paradigmatic changes. Our research on designers and major actors in the fashion design industry shows that branding of fashion designers takes new routes, and we observe a subculture that is resistant to standardisation and proposes niche markets supported by networks and new intermediary actors. The cooperation of networks and intermediary actors appears essential for the development of these creative careers, through knowledge exchanges and collaboration. We highlight the role of these collective actors, networks and organisations in supporting designers in access to knowledge and career development.

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)0.006
metaresearch head score (Gemma)0.025
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 score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.005
Scholarly communication0.0090.005
Open science0.0010.009
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0190.001

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 head0.071
GPT teacher head0.353
Teacher spread0.283 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

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