Master's students, enrolled in the Department of Informatics and Media at Uppsala University, along with doctoral candidates and researchers, affiliated with SDCI Gothenburg, are actively working with JobTech Development’s open APIs and datasets with the goal of finding solutions to actual problems in the job market. The students from Uppsala University are conducting a detailed analysis of challenges in the Swedish labour market, including biases in recruitment, CVs, forecasts, and the significance of soft skills in the recruitment process. In addition, researchers at SCDI Gothenburg are exploring the correlation between the availability of open data and its potential positive impact on the labour market.

Linking Open Data to Enhance Long-term Effects on the Labour Market

Ph.D. candidates and researchers at SCDI Gothenburg will try to investigate whether making open data accessible results in a positive impact on the labour market. The case study will be based on the utilization of open data as a tool to measure the long-term effects on the labor market.

The case study will be built on two variables:

1. The first variable involves the understanding how the labour market and its matching efficiency function by analysing data, segmented by factors such as regions and industries, among others.
2. The second variable is constructed based on JobTech Development’s activity and given contributions to the labour market, such as the introduction of a new API or dataset, which can play a role in relation to the functioning of the labour market. Additionally, one can assess the number of API calls over a period, per component, and region.

Furthermore, the hypothesis can be developed on providing an overview of how the distribution between Platsbaken (the Swedish National Job Board) and other job platforms has evolved over time in relation to the number of job advertisements or, alternatively, job matches. Is there any specific pattern?

Working with and testing the JobTech Development’s open components is not new for the researchers and students at SCDI Gothenberg. They leverage their previous projects and implement lessons learned to this case study.

Johan Magnusson, Professor, Director, SCDI Gothenburg

"We have integrated Jobtech Development into our courses, where students work on utilizing the data and the development environment to create apps and services spanning through skills supply, job matching, and educational design. The students appreciate the simplicity and clarity, offered by JobTech Development. Furthermore, JobTech Development is seamlessly integrated into our research.", says Johan Magnusson, Professor, Director, SCDI Gothenburg.

Business Models Based on Bias in Recruitment, Forecasts, and Soft Skills

In the classroom, master’s students at Uppsala University are exploring various open data sources, including JobTech Developments’s open data, in order to outline, design and build their business models. By utilizing different datasets, they gain a broad and versatile informational foundation that can provide a better understanding of the labour market dynamics, trends, and requirements. Additionally, students are assigned to integrate and explore the incorporation of open-source code as a pivotal element in their business models.

"In past years (2022), students have experimented with JobTechs APIs and provided feedback on standardization and documentation related to the APIs. A strength of our students is that most of them have professional work experience, allowing them to contribute with valuable expertise. Additionally, their ability to approach existing data and challenges from a new, fresh perspective enables them to suggest solutions.", says Claire Ingram Bogusz, Senior Lecturer/Associate Professor at the Department of Informatics and Media, Uppsala University.

Concrete challenges in the labour market:

1. Bias in recruitment: the challenge is to identify and address bias problems during recruitment in order to create a fair and inclusive labour market.
Decisions are influenced by unconscious biases and preferences instead of being based on objective assessments of candidates' competence. It can lead to discrimination, creating inequalities in the labour market, inhibiting innovation, productivity, and workforce diversity. By using objective assessment criteria, expanding recruitment networks, and raising awareness of bias, a fairer and more equal recruitment process can be promoted.

2. CV bias during recruitment: the challenge is to limit bias and create a fairer assessment of candidates by overcoming the limitations with the CVs.
CV can be a source of bias and discrimination; job candidates can give a limited picture of their capabilities in a CV, which can lead to exclusion of competent candidates and a lack of diversity in the workforce. Difficulty verifying the information in the CV can also create uncertainty about a candidate's actual competence and suitability. By using structured interviews, assessment tests, and other tools that provide a more comprehensive picture of candidates' abilities and competencies, a fairer and more inclusive recruitment process is promoted.

3. Forecasts: the challenge is that forecasts in a fast-changing labour market are influenced by uncertainty and complexity.
Changes in skill requirements occur rapidly due to technological advances and changes in working life. This means that forecasts can be outdated and misleading. The consequences can be significant: a poor match between education and labour market, unemployment or underutilization of skills, lack of inclusion and equality, among others. By using a wider set of data sets, labour market analyses, expert judgments and feedback from various stakeholders, educational and career choices can be supported, and fair labour market opportunities promoted.

4. Screening employers: the challenge is lack of opportunities for jobseekers to screen companies to create a more transparent and fair recruitment process.
Job seekers may find it difficult to assess the company's financial position, work environment, leadership, and values. This can lead to a poor matching of values and the risk of ending up in unfavorable work environments. The situation makes it difficult to assess career opportunities and make informed decisions. By providing solutions for validation and standardized assessment of companies, a fairer and more transparent recruitment process can be created as well as a better and more sustainable matching between jobseekers and employers promoted.

5. Soft skills: the challenge is to promote the value of soft skills during recruitment for a more dynamic and inclusive workplace.
Soft skills are non-technical skills that affect how you work, interact with colleagues, manage work, and tackle problem solving. Today, soft skills are valued relatively low in recruitment. It can lead to a lack of diversity and inclusion in the workplace, missed potential of candidates, difficulties in creating effective teams and a limited ability to adapt in a changing work environment. By including soft skills in job advertisements, using behavior-based assessment methods, or evaluating candidates' soft skills in a more comprehensive way, a more transparent and fair recruitment process can be promoted.

Claire Ingram Bogusz, Senior Lecturer/Associate Professor at the Department of Informatics and Media, Uppsala University

"Using open data and APIs means that we apply both enriched datasets and address concrete problems. This approach allows us to outline and design our teaching and project processes to reflect the reality. Students need to acquire the skills to navigate complexity and make informed decisions in today's dynamic job market. The hypothetical data and case studies commonly used in educational activities can at times be overly simplified and/or illustrative.", highlights Claire Ingram Bogusz.

On the JobTech Development platform, all components are free of charge and available for anyone to use. The aim is to encourage partnerships with other universities, so that various academic institutions can show interest in the technical components.