Data and Reproducibility

Data and Reproducibility Policy — Selaparang: Journal of Law Studies (SEJALS)

To promote transparency, integrity, and open science within legal scholarship, Selaparang: Journal of Law Studies (SEJALS) encourages authors to share the data, empirical materials, statutory documents, case law references, and research instruments supporting the findings reported in their published articles, whenever appropriate and feasible.

1. Scope and Applicability

  • Empirical and Socio-Legal Research: For articles employing empirical methods (such as quantitative surveys, qualitative interviews, observations, or socio-legal field research), authors should be prepared to share anonymized primary datasets or documentation upon reasonable request from the editors or qualified researchers, provided that ethical, privacy, and confidentiality constraints are respected.
  • Normative and Doctrinal Research: For traditional normative legal research, doctrinal analysis, and statutory interpretation, reproducibility is achieved through precise citation, transparent legal reasoning, and accurate references to primary legal sources (such as constitutions, statutes, court decisions, international treaties) and secondary authorities (such as scholarly books, journals, and legal commentaries).

2. Data Availability Statement

  • Authors conducting empirical or data-driven legal research are encouraged to include a Data Availability Statement in their manuscript, indicating whether and where data can be accessed.
  • If data cannot be publicly shared due to ethical, legal, or privacy restrictions (e.g., sensitive human subject data or confidential court records), authors must explicitly state the reasons for such restrictions in the manuscript.

3. Research Ethics and Participant Confidentiality

  • In empirical legal studies involving human participants (e.g., interviews with vulnerable groups, victims, or state officials), data sharing must strictly comply with ethical standards, participant confidentiality, informed consent agreements, and applicable data protection laws.
  • Personal identifiers must be thoroughly anonymized or removed before any dataset is shared or archived.