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Record W6996939874

The Threads, Trends and Threats of the Wedding Dress:
\nA Collaborative, Studio-based Dissertation

2016· dissertation· en· W6996939874 on OpenAlexfundno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2016
Typedissertation
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsnot available
FundersUniversidad Autónoma del Estado de MorelosConcordia University
KeywordsEthnographyMetaphorEmbodied cognitionPopular cultureWhite (mutation)Visual cultureSubject (documents)Social practice
DOInot available

Abstract

fetched live from OpenAlex

A multi-faceted, collaborative studio-based project of doctoral research-creation, this thesis uses art, text, textiles, photographs and the body to explore how visual culture participates through dress in the creation of female stereotypes and, as an informal educative practice, contributes to the definition of feminine identities. It is centred on the participation of 19 women who guided the artistic transformation of wedding dresses to represent their different notions of marriage. This project allowed participants to experience the research-creation inquiry in both personal and social contexts, responding creatively through visual, material and embodied thinking. Conceptualizing and representing our experiences through dress and text, we developed new understandings about close relationships and community through imagination and intellect. Brides function here as representative stereotypes of femininity, while wedding dresses work as a metaphor for marriage in exploring the restraining symbolisms hidden in the form of tradition that certain current cultural and social rituals have for women. Based on collaborative research-creation processes and supported by inclusive ethnographic methods, this thesis intends to develop new understandings and awareness about the connection of fashion and popular visual culture to the ways women learn and generate meaning. The project was inspired by “Trash the Dress” (TTD) wedding photography, a relatively new and increasingly popular practice in North America which shows brides wearing their white dress in an environment outside of the traditional wedding context, damaging or destroying it, or even exposing themselves during the session—a cultural phenomenon just now beginning to attract the attention of theorists, scholars and artists. Through collaborative artistic processes, this project explores how femininity is influenced by popular and media representations of women as brides, considering personal issues related to love, commitment, family, tradition, and religion, and also the social challenges, responsibilities and negotiations that women face in conjugal relationships. Based on visual and textual analyses of participants’ transformed and embodied dresses and their responses to survey questions, the thesis concludes that working in collaboration with others can provide a context for personal learning and social growth, allowing participants to creatively explore their experiences together and to discuss and develop new ideas. Thus, The Threads, Trends and Threats of the Wedding Dress considers close relationships and love both as our subject of study and as a strategy to create new knowledge and ways of knowing through art-education in ways that allow for compassion, awareness and humanization.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.032
GPT teacher head0.292
Teacher spread0.261 · 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 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
Published2016
Admission routes1
Has abstractyes

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