Women in Male-Dominated Industry :The Construction Industry : A Study of Women's Disinterest, Professional & Social Barriers, Walkout from Construction Industry.
Bibliographic record
Abstract
Problem: Many women experience problems when trying to enter the construction industry and perceive several barriers in professional practice. As a result, day by day women are losing their interest in building their career within this male-dominated industry and diverting towards other professions. The fact that women are showing less interest to work within construction industry and leaving the industry has been found as a major problem. Since in this male dominated industry around ninety percent labour are men and expecting a large numbers of retirement in the future, therefore today’s construction industry has a strong demand for labour. The construction industry’s representatives want to increase the number of women in this trade, but because of the previous reputation and discriminatory work environment it’s become difficult to attract more women. Therefore, to enhance the participation of women in construction trades, it is necessary to understand women’s perceptions about the nature of work and level of satisfaction or dissatisfaction with the job. It is also important to know what kind of changes in the work environment can motivate women not to leave this industry? How to eliminate the barriers in professional practice? Purpose: This thesis explores the current position of women in construction industry, and seeks to identify the reasons of women’s disinterest about the industry, job satisfaction and the barriers (professional and social) that compel women to think to change career and leave the construction industry. Method: This study has been performed through a qualitative interview study based on themes, on the subject of women in male-dominated industry. The research data is collected by conducting semi-structured interviews with professionals from Sweden, the USA, Canada, Latvia, Greece, The Netherlands and Bangladesh. The participants were active within the construction industry, and had the designation of project manager, construction engineer or structural engineer. To analysis the data in this research the Thematic Analysis approach has been adopted. Findings: The interviewed women stated that the unpleasant work environment, gender discriminatory behaviours from the male colleagues, less career development opportunities, unfair promotion system and unequal salary compel them to rethink about their career choice and leave the construction industry. The results of this study showed that the barriers women face in professional practice also depends on the geographical position and societal culture.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".