Training course on Ethical Considerations in Social Protection Data and M and E

Training Course on Ethical Considerations in Social Protection Data and M and E

Introduction

Ethical Considerations in Social Protection Data and Monitoring and Evaluation (M and E) is a paramount and increasingly critical area of focus, recognizing that social protection programs often involve collecting and utilizing highly sensitive personal data from vulnerable populations. While data and M and E are essential for accountability and learning, they also carry significant risks related to privacy, discrimination, potential harm, and misuse of information. This course moves beyond technical aspects to deeply explore the moral and professional responsibilities of all actors involved in social protection data management and evaluation. It emphasizes that upholding ethical principles is not merely a compliance issue but a fundamental imperative for safeguarding human rights, building trust, and ensuring that social protection interventions genuinely serve the best interests of their beneficiaries.

Training Course on Ethical Considerations in Social Protection Data and M and E is meticulously designed to equip with the advanced theoretical insights and intensive practical tools necessary to excel in Ethical Considerations in Social Protection Data and M and E. We will delve into the foundational principles of research ethics and human rights, master the intricacies of informed consent, data privacy, and confidentiality, and explore cutting-edge approaches to algorithmic bias, data governance, and grievance redress mechanisms. A significant focus will be placed on hands-on application, analyzing real-world complex ethical dilemmas, and developing practical strategies to ensure that all data and M and E activities are conducted with the highest standards of integrity, respect, and responsibility. By integrating industry best practices, analyzing complex case studies, and engaging in interactive discussions, attendees will develop the strategic acumen to confidently champion and implement ethical data and M and E practices, fostering unparalleled trust, accountability, and human dignity in social protection.

Course Objectives

Upon completion of this course, participants will be able to:

1. Analyze the fundamental ethical principles and human rights frameworks relevant to social protection data and M and E.
2. Comprehend the strategic importance of ethical conduct for building trust and ensuring program effectiveness.
3. Master the principles and practices of informed consent in diverse social protection contexts.
4. Develop expertise in ensuring data privacy and confidentiality for sensitive beneficiary information.
5. Formulate strategies for identifying and mitigating potential harm and unintended consequences of data and M and E.
6. Understand the critical role of addressing bias and discrimination in data collection, analysis, and algorithmic applications.
7. Implement robust approaches to data governance and accountability mechanisms for ethical data use.
8. Explore key strategies for ensuring transparency and responsible communication of data and M and E findings.
9. Apply methodologies for establishing effective grievance redress mechanisms for data subjects.
10. Understand the ethical considerations specific to vulnerable populations (e.g., children, refugees, persons with disabilities).
11. Identify potential ethical dilemmas in social protection data and M and E.
12. Learn techniques for data anonymization, pseudonymization, and aggregation.
13. Explore sources of bias in data (e.g., sampling bias, measurement bias, algorithmic bias).

Target Audience

This course is essential for all professionals involved in social protection data and M and E:

1. M and E Specialists & Data Managers: Directly handling data and evaluation activities.
2. Social Protection Program Managers: Responsible for program design and implementation.
3. Policymakers & Government Officials: Shaping data policies and regulations.
4. Legal Professionals: Advising on data protection and human rights.
5. Development Practitioners: From NGOs and international organizations.
6. Researchers & Academics: Conducting studies involving human subjects.
7. Civil Society Organizations: Advocating for rights and ethical practices.

Course Duration: 5 Days

Course Modules 

Module 1: Foundations of Ethics in Social Protection Data and M and E

• Define core ethical principles: respect for persons, beneficence, non-maleficence, justice.
• Explore relevant human rights frameworks (e.g., UDHR, ICESCR, CRPD) and their data implications.
• Discuss the unique ethical landscape of social protection, involving vulnerable populations.
• Understand the importance of building trust and legitimacy through ethical conduct.
• Identify potential ethical dilemmas in social protection data and M and E.

Module 2: Informed Consent: Principles and Practice

• Master the principles of informed consent: voluntariness, comprehension, disclosure.
• Learn to design and implement informed consent processes for diverse contexts.
• Address challenges in obtaining consent from vulnerable populations (e.g., illiterate, children).
• Understand the nuances of broad consent vs. specific consent for data use.
• Practice developing informed consent forms and scripts 

Module 3: Data Privacy and Confidentiality

• Develop expertise in ensuring data privacy and confidentiality.
• Differentiate between privacy, confidentiality, and anonymity.
• Learn techniques for data anonymization, pseudonymization, and aggregation.
• Understand secure data storage, transmission, and access protocols.
• Discuss compliance with data protection regulations (e.g., GDPR, national data protection acts) 

Module 4: Mitigating Harm and Addressing Bias

• Formulate strategies for identifying and mitigating potential harm (physical, psychological, social, economic).
• Understand the concept of "do no harm" in data collection and use.
• Explore sources of bias in data (e.g., sampling bias, measurement bias, algorithmic bias).
• Learn techniques for detecting and addressing algorithmic bias in targeting and predictive analytics.
• Discuss strategies to prevent discrimination and stigmatization through data.

Module 5: Data Governance and Accountability

• Implement robust approaches to data governance for ethical data use.
• Discuss the roles and responsibilities of different actors in data stewardship.
• Establish clear data sharing agreements and protocols.
• Understand the importance of independent ethical review boards.
• Explore mechanisms for accountability when ethical breaches occur.

Module 6: Transparency and Responsible Communication

• Explore key strategies for ensuring transparency in data collection and use.
• Learn to communicate data and M and E findings responsibly and ethically.
• Discuss avoiding misleading visualizations and overstating impacts.
• Understand the importance of clear, accessible communication about data practices.
• Practice ethical data storytelling and reporting.

Module 7: Grievance Redress Mechanisms (GRMs)

• Apply methodologies for establishing effective grievance redress mechanisms for data subjects.
• Understand the importance of accessible and trusted channels for complaints.
• Learn to design processes for handling data-related grievances.
• Discuss the role of GRMs in upholding accountability and trust.
• Analyze case studies of GRMs in social protection.

Module 8: Ethical Considerations for Vulnerable Populations

• Understand specific ethical considerations when working with vulnerable groups.
• Discuss child protection protocols in data collection.
• Explore ethical approaches for refugees, IDPs, and migrants.
• Address considerations for persons with disabilities and marginalized communities.
• Learn to adapt ethical practices to diverse cultural contexts.

 

Training Methodology

• Interactive Workshops: Facilitated discussions, group exercises, and problem-solving activities.
• Case Studies: Real-world examples to illustrate successful community-based surveillance practices.
• Role-Playing and Simulations: Practice engaging communities in surveillance activities.
• Expert Presentations: Insights from experienced public health professionals and community leaders.
• Group Projects: Collaborative development of community surveillance plans.
• Action Planning: Development of personalized action plans for implementing community-based surveillance.
• Digital Tools and Resources: Utilization of online platforms for collaboration and learning.
• Peer-to-Peer Learning: Sharing experiences and insights on community engagement.
• Post-Training Support: Access to online forums, mentorship, and continued learning resources.

 

Register as a group from 3 participants for a Discount 

Send us an email: info@datastatresearch.org or call +254724527104

Certification

Upon successful completion of this training, participants will be issued with a globally recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs. 

Key Notes

• Participants must be conversant in English.
• Upon completion of training, participants will receive an Authorized Training Certificate.
• The course duration is flexible and can be modified to fit any number of days.
• Course fee includes facilitation, training materials, 2 coffee breaks, buffet lunch, and a Certificate upon successful completion.
• One-year post-training support, consultation, and coaching provided after the course.
• Payment should be made at least a week before the training commencement to DATASTAT CONSULTANCY LTD account, as indicated in the invoice, to enable better preparation.