Imparting industry relevant skills through skill development initiatives in the apparel industry: a literature review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The global apparel market is positioned at US $1.7 trillion, approximately 2% of the world's GDP and is expected to reach US $2.6 trillion by 2025. In India, this sector contributes 11% to exports and 4% to the gross domestic product. It is the second largest employment generating sector and to remain globally competitive, it requires a huge skilled human resource. The training programs provide industry relevant skill trainings. The current paper conducts a systematic review of literature covering publications and studies on global skill development initiatives. It also aims to identify the directions for further research after studying 90 publications during the period of 1991-2020. It identifies the skill gaps in the job role of sewing machine operator (SMO) in the apparel sector in India. Through the content analysis, this paper identifies three skill constructs that impact the employability of the candidates after completion of such training programs.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it