Sentence examples for gender qualification from inspiring English sources

The study investigated the influence of demographic factors on stress perceptions of teachers of secondary schools, examined factors causing stress and the influence of gender, qualification, experience cultural background, school location and size on stress perceptions of teachers.

There are different possible explanations for occupational career patterns (Bender et al. 2000): on the one hand, there are contextual factors related to the family of origin (Schulenberg et al. 1984), and on the other hand, there are individual characteristics (e.g., gender, qualification, age) and motives (e.g., parenting).

However, we were not bold enough to say that these variations came as a result of socio-demographic and background characteristics differences among the groups like gender, qualification, accessing education and training on VBC.

At Barclays, we're dedicated to equality in the workplace and rather than focusing on gender, qualifications or past experience, we look for candidates who show real potential.

The right to vote for the Legislative Assembly was reintroduced in 1936, but property, literacy, and gender qualifications severely limited the franchise.

Gender, qualifications and labour force experience are standard variables to include in labour force analyses.

Section A gathered demographic details on participants such as age, gender, qualifications, level of clinical experience, research training and current work status.

A range of demographic information was also collected about each participant pre-intervention, including: age, gender, qualifications, role, length of time working in the facility, and number of hours worked.

As these dependent variables might also be influenced by their gender, qualifications, etc., those basic characteristics were also included in the multivariate models, except for the practicing method, which was not significant in the univariate and multivariate regression models.

Our study did not assess the play of other factors that may be predictive of improved response to non-monetary incentives (e.g. age, gender, qualifications etc) and this could be the focus of further studies.

**Model 2 variables: gender, ethnicity, qualification region, qualification year.