Analysis on Students’ Performance to Promote Gender Equality in Creative Fashion Design
Bibliographic record
Abstract
The fashion industry has prospects and it can help to project the economy to compete with the international market. However, the extent of gender imbalance emerging from the Fashion Department of Kumasi Technical University is becoming a threat to the future of the industry. This paper is aimed at creating awareness of the extent of gender imbalance and promoting the inclusion of more male fashion students in fashion institutions. This was achieved by conducting an analysis of gender performance in Creative fashion design processes. The study employed educational Design and Quantitative research methods with a descriptive style of analysis. With a sample size of n=191, a structured questionnaire was distributed to participants on different occasions during class hours to gather relevant data for the study. The results showed that, though the female students were more than the male students, the male students performed better than the female students in terms of creative fashion design processes. Most of the students were of the opinion that the famous fashion designers in history and the present day are men. Also, most of the students responded that the best fashion designers in their locality are men. The study recommends that society needs to be educated and encourage more male students to take up fashion as a career.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".