Public repository to share resources from the OLS project on 'Widening Participation in Higher Education' funded under the Turing's Skills Policy Award.
Diversity amongst staff and students in higher education is demonstrably unequal,
both in gender balance and ethnic balance.
Numerous national and international studies highlight that women, certain ethnic minorities, people with disabilities and those from disadvantaged socioeconomic backgrounds are underrepresented in education, training and employment related to STEM.
Open science and open source movement has enabled enhanced equity and inclusion of underrepresented groups in research and technology.
Nonetheless, even in open source, software developers self-report to be over 90% male and only
15% self-report as BME.
With growing applications of data science and AI technology in decision making and automation, as per ONS analysis, women and young people are most at risk of unemployment. It is unsurprising that lack of diversity among tech workforce directly reflects on the technology and continues to disadvantage populations from marginalised communities who already experience systemic barriers to participation.
Through this project, OLS aims to address the above described challenge by diversifying skills for the next generation of diverse workforce. This work will strengthen the use of open source and open data practices and offer a resource to recognise opportunities to take new career directions. By engaging with policy landscape, this work will support investments and funding for collaboration, leadership and entrepreneurship to widen participation.
OLS’ goals and operations directly align with the theme of ‘widening participation’. OLS embodies principles of EDIA and is deeply committed to achieving AI and data literacy for everyone, operationalising the AI Council Roadmap recommendations mentioned under this theme.
Full proposal can be read on Zenodo: zenodo.org/record/7602717. To cite this document, please use:
OLS team. (2023). Submission by OLS team for the the Skills Policy Awards 2023/2024. Zenodo. https://doi.org/10.5281/zenodo.7602717
- Set up a public repository to share resources
- Set up an internal data storage to protect research data under GDPR regulation
- Publish the project proposal on Zenodo
- Set up finance management process to receive the Turing Skills Policy Award
- Set up a timeline and deliverable document
- Set up agreements with the fellows involved in this project
- Create a project charter to provide stakeholders information and define nature of engagement
- Set up data management plan (GDPR compliance)
- Deliverable 1.1 - Expert Consutation (UK)
- Stakeholder mapping
- Shortlisting and invitation
- Conduting interview/consulation
- Summarising interview notes
- Drawing key points for the Deliverable 3
- Deliverable 2 - Policy review research preprint
- Each contributor to the project carries out literature review
- Combine each review in a shared draft
- Review the draft (project team)
- Invite community review of the draft (preprint)
- Submit preprint for peer-review publication
- Deliverable 3 - Policy Briefing Note
- Combine insights from the literature review and expert consultation
- Define the scope and structure of the policy briefing
- Allocate different section of the policy briefing to each project member
- Review and edit the full draft (project team)
- Deliverable 1.2 - Expert Consutation (international)
- Stakeholder mapping
- Shortlisting and invitation
- Conduting interview/consulation
- Summarising interview notes
- Drawing key points and add to the Deliverable 3
- Key publication of the policy briefing note
- Invite community review of the draft
- Submit briefing note to reevant bodies/platforms
- Present outcomes to the national and international audience
This repository is jointly developed and maintained by the following OLS team members:
- Yo Yehudi: Project lead; OLS Executive Director
- Mayya Sundukova: Resident Fellow
- Flavio Azevado: Resident Fellow
- Malvika Sharan: Co-Director
- OLS Team as contributors
The Mentor assigned to this project is: TBA
For any question, please email the OLS team [email protected]. You can also directly reach out to Yo by emailing [email protected].
Please create an issue to share references or ideas related to the development of this project.
This project will be conducted collaboratively and utlising open science practices. This means that we will transparently communicate the project's goals, roadmap, status, methods and opportunities for collaboration. All non-sensitive data and resources from the project will be shared on this GitHub repository. We will closely follow the GDPR checklist to manage consent for GDPR compliance.
- Add a README file
- Add a CONTRIBUTING file
- Add a LICENSE
- Add a Code of Conduct
- Install all-contributors bot
- Create a directory with files for project management (meetings, report, proposals)
- Create a directory with files for communications
- Create a directory for research data
- Create a directory for research results/outcome to share (?)
- Connect repo with Zenodo
- Add cff file for citation
- Add badges
This repository contains the following directories and files.
├── LICENSE
├── README.md <- The top-level README for users of this project.
├── CODE_OF_CONDUCT.md <- Guidelines for users and contributors of the project.
├── CONTRIBUTING.md <- Information on how to contribute to the project.
├── data
│ ├── processed <- The wrangled and cleaned data sets for analysis.
│ └── raw <- The original unprocessed data.
│
├── docs <- All project related documents to share
│ └── reports <- Regular report document
│
├── project_management <- Meeting notes and other project planning resources
│ └── communications <- Communications materials related to the project
└──
This repository uses the Template repository provided by The Turing Way Team: github.com/alan-turing-institute/reproducible-project-template.
This work is licensed under the MIT license (code) and Creative Commons Attribution 4.0 International license (for documentation). You are free to share and adapt the material for any purpose, even commercially, as long as you provide attribution (give appropriate credit, provide a link to the license, and indicate if changes were made) in any reasonable manner, but not in any way that suggests the licensor endorses you or your use, and with no additional restrictions.