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Record W4310836565 · doi:10.32920/21688970

A study of Canadian female baby boomers: Physiological and psychological needs, clothing choice and shopping motives

2022· preprint· en· W4310836565 on OpenAlexaffabout
Osmud Rahman, Hong Yu

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsClothingBaby boomersGratificationConsumption (sociology)PsychologyAdvertisingProduct (mathematics)AttractivenessPopulationMarketingApplied psychologyGerontologySocial psychologyBusinessMedicineSociologyPolitical scienceDemographySocial scienceEconomics

Abstract

fetched live from OpenAlex

<p>The purpose of this paper is to gain an understanding of baby boomers’ physiological and psychological needs through clothing consumption.</p> <p>This study intended to offer new knowledge on the issues of baby boomers’ unmet needs, and provide insights and implications to fashion practitioners. A qualitative research approach was employed for this study. Data were collected from two generational segments: early baby boomers (1946–1954), and late baby boomers (1955–1964). In total, 13 informants aged from 53 to 71 years were participated in this study. Content analysis and interpretive approach were used for data analysis. According to the findings, there are several reasons why the baby boomers shopped for clothing, including a way of stress relief or retail therapy, wardrobe update, replacement of worn-out garments, attractiveness of clothing styles and convenience. Style, fit, comfort and colour were the four most important product evaluative cues. Other than product cues, age appropriateness is an important factor for clothing consumption. Many informants were disappointed with their current body type, shopping experience and the industry offers. Age-appropriate clothing can give wearers greater self-assurance/-gratification. If fashion designers create their products based on the baby boomers’ cognitive age, it would probably increase their customers’ acceptance and satisfaction. The rapid growth of the aging population is a global phenomenon. Therefore, investigating the needs and challenges of the baby boomer generation is both timely and imperative. </p>

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.997

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.238
GPT teacher head0.322
Teacher spread0.084 · 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 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

Citations5
Published2022
Admission routes2
Has abstractyes

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