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Introduction
O Reglab Methodology Manual is a guide to standardize, clarify and
ReplicabilityMethodologically strict data structure, collection and analysisTransparencyOpen and available methodology tableCredibilitySource verification bias reduction procedures
strengthen the methodological practices of our studies. It is a reflection of our commitment to rigorous, transparent and evidence-based research.
Reglab is a think tank specialized in consultancy and applied research. The way we develop our work matters, and that is why we conduct our studies rigorously, to highlight an essential aspect of our work:
the commitment to evidence-based research.
Our objective is to produce knowledge that influences decisions, whether business or public policy. Therefore, we consider it our duty and part of our mission to adopt three essential guidelines in all our activities:
- Application of a structured and replicable research method; and
- Methodological transparency, including research limitations; and
- Credibility, with bias reduction procedures and consolidated methods.
In the following pages, we will show how we apply these guidelines in practice.
We divide this guide as follows:
- What are our survey formats?
- How do we do our research?
- How do we ensure transparency about our methods?
Finally, the idea of publishing this document is also to serve as an internal and invitation for other organizations, companies and think tanks adopt similar practices, promoting a culture of excellence and transparency in research.
Our research initiatives are divided as follows:
Public
These are surveys publicly disclosed on our website. The objective is to promote relevant research findings, whether new or not, that can have a practical impact on the community.
Private
These are studies contracted by specific clients, kept confidential as they involve strategic or confidential information. For example:
- a benchmark analysis, evaluating the market and competition;
- a regulatory impact report specific to a company’s operations;
- a collection of legal data specific to a client’s litigation strategy.
By contract
Commissioned Studies
These are customized surveys with scope and deliveries defined by the contractor, carried out under strict quality standards, which include, at a minimum, the following practices:
- autonomy in analyzing the final results (the client can contribute to the definition of the problem, research questions and methods, but does not interfere in the study conclusions)
- transparency about funding sources, methodology and procedures to reduce bias
Digital Policy Hub
Studies in which Reglab maintains methodological control within a sponsored line of research. Reglab determines the scope, objectives and methodology of the research, with sponsoring companies having a limited role. This format differs from commissioned formats due to greater editorial independence.
Institutional
Independent research by Reglab or guest researchers on strategic topics of public interest. These initiatives are developed with our own resources, preserving editorial and methodological autonomy.
Reglab Radar
Policy Briefs
presents visual reports that combine qualitative and quantitative data, offering a contextualized view of specific phenomena. Radar Reglab seeks to synthesize complex information in an accessible way, facilitating the understanding of emerging trends and agendas with visual resources and graphic design.
studies that evaluate existing or proposed public policies, to inform and guide strategic decisions.
This is research that seeks to synthesize complex issues in an accessible way, highlighting the main points of analysis, impacts and possible recommendations.
Discussion Papers
These are preliminary documents that present initial results of ongoing research, from Reglab or third parties. They should include a “Research Questions and Provocations” section to encourage feedback and constructive criticism, even if they do not follow all Reglab methodological standards.
Reglab Context
concise summaries that summarize specific topics or emerging trends.
Designed to present information in a clear and accessible way, incorporating visual elements such as graphs, tables and infographics, combining analytical rigor with practicality.
Reglab Tests
covers articles by guest authors who explore themes
of digital governance, synthesizing research, presenting empirical evidence or new information for the debate. The texts follow Reglab’s standards of methodological transparency, being the responsibility of the authors.
These are deliveries (generally commissioned) that do not fit into the previous categories and represent customized solutions for specific clients, where Reglab’s expertise offers a differentiator. Examples include:
- Euias “Doing Business” sectorial or comparative analysis of legislation.
- Customized regulatory compliance manuals for specific sectors.
- International regulatory mapping reports for new markets.
- Frameworks regulatory risk assessment for emerging technologies.
- Practical guidelines for implementing new regulations.
- International reports from benchmark.
How do we do our research?
In this section, we’ll talk about how we structure methods. It’s not a general research manual – there are good ones out there. Just tell us how we do it.
The question and research structures
A good research question should be clear, specific and relevant, directing the team’s efforts to obtain answers.
A research question isthe starting point that guides the entire process, defining the problem to be solved and the focus (outline) of our work.
In a report on technology regulation, a question could be: “What are the impacts of changes to the Marco Civil
of the Internet for freedom of expression and legal security in Brazil?”
Questions help define the research structure and the concept map that connects theory, data and methods to build an organized response. At Reglab, we adopt methodologies that favor rigor and clarity, accessible to companies, policymakers and the general public.
Below are examples of structures and their relationship to research objectives and questions:
Exploratory research
Discover and Contextualize
It seeks to investigate little-studied or unknown phenomena, aiming to raise hypotheses, identify trends and expand initial understanding
on a topic, without seeking definitive conclusions. They are typically inductive.
Action research
Evaluate
It involves study participants in the research process, seeking to solve practical problems while generating knowledge.
Comparative analyzes before and after interventions (e.g. training) fall into this category.
Discover and Compare
Systematic and rigorous review of results and previous studies on a topic, combining data to identify patterns and consistency of evidence. Literature reviews fit here.
Historical research
Contextualize and Evaluate
Longitudinal studies that investigate past events to understand their evolution, causes and consequences. Focuses on the analysis of records, documents and historical data.
Comparative research
Compare and Evaluate
Compares two or more phenomena, with definition of control factors, seeking to identify similarities
and differences. Used to generate knowledge about contextual variations in different scenarios. They are typically deductive.
Case study
Contextualize
Detailed and in-depth analysis of a single specific phenomenon, seeking to understand its particularities.
Ideal for generating inferences about highly complex situations.
Data Collection
The section of data collection is one of the most important stages of any research. This is where we ensure that the information used is relevant, reliable and aligned with the objectives of the study.
At Reglab, we treat this stage with rigor and transparency, seeking to ensure quality and methodological consistency. We always discuss, before any research, our data universe, to general approach and the collection method.
The data universe
Before starting collection, it is necessary to establish the data set to be analyzed. This includes identifying the types of sources and documents (such as reports,
studies, public records or interviews) and the inclusion and exclusion criteria. This step ensures that collection is targeted and that the data reflects the scope defined by the research question.
When analyzing a court case, the procedural documents may not be sufficient to answer the question, for example. In this case, we will study how to expand this universe, including news in the press.
The approach: deductive or inductive?
In some research, we have so much data that it is necessary to have a specific focus, otherwise we can get lost in useless information.
In others, obtaining it is part of the challenge, and many things will be discovered from this.
Therefore, we always try to reflect: Are my research goals clear enough, or will the act of research itself help me figure it out?
- If my goals are already well defined, you probably need to adopt an approach deductive. We start with an established hypothesis and look for specific data to test it.
It’s like having a detailed map before your journey – you know what you’re looking for and where you’re going – although you may change your mind along the way. For example, creating previous categories in a table to analyze a process is a typical deductive approach.
When my goals are unclear and the topic is unknown:
you probably need to adopt an approach inductive, starting to explore the data
available to identify patterns and formulate hypotheses later.
For example, when studying the impact of a new technology on society,
We collect different data (interviews, documents, statistics) and only then identify trends and draw conclusions about their effects.
Thematic selection and preliminary research
Thematic selection and preliminary research
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Develop and test hypotheses
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This distinction between approaches is important because it defines the method and way in which
we relate to customers and partners. Commissioned studies generally use a deductive approach to validate pre-established hypotheses, while research on emerging technologies follows inductive methods to identify new patterns.
The clarity of the approach also aligns expectations: Deductive projects allow for fixed schedules, while inductive projects require more flexibility.
The collection methodology
A collection methodology describes how the data will be obtained.
It’s more than gathering information — it’s building a robust foundation for evidence-based analysis.
The clarity and systematization of this stage are fundamental to the quality, credibility and practical impact of the research. Documenting each step in detail – from defining sources to selection criteria and tools used – creates a roadmap that allows other researchers to understand and reproduce our process.
general approach, universe of data, objectives and research questions.
At Reglab, we consider a well-documented collection process critical for robust analysis and reliable recommendations. Defining the collection method involves identifying the
Qualitative
Quantitative
Some methods we use include:
Qualitative interviews
What do you think… / In your opinion, how does it work… Format that explores individual insights in depth, collecting detailed data about experiences. Ideal for complex topics (Expert Interviews) or audience insights (Reception Studies).
Focus groups
What do you think… / In your opinion, how does it work… Group discussion to understand collective opinions on a specific topic,
promoting interaction. It seeks to confront attitudes and deepen behaviors.
Participant observation
What’s happening… / How’s it happening… Method where the researcher gets involved in the environment
studied, observing behaviors in a natural context. Ideal for legislative processes, stakeholder analysis and “on the go” discussions
(e.g. social media).
Netnography
How, in practice, do people do Structured, quantitative or sampling analysis of the behavior, interactions and cultures of groups on online platforms, such as social networks and forums, exploring practices and meanings shared in digital environments.
Surveys and questionnaires
How much they say happens… Structured quantitative data collection tool, used to measure opinions or behaviors on large bases.
Not recommended for complex themes.
Document analysis
What a person does… / How a person does… Systematic examination of texts and records to identify patterns and insights
about the object of study. Ideal for regulatory and judicial analysis, comparative assessments, press discourse and stakeholder positioning.
Analytics and statistics
How much happens… Analysis of numerical data to identify patterns, trends and correlations, generating objective insights.
Data Analysis
The section of data analysis it is the interpretative core of research, where the collected data is processed and transformed into significant findings.
Despite its importance, this stage is often neglected in Law studies. Legal education rarely includes courses on data analysis methods, and this phase often becomes “cherry picking” – a problematic practice, in which data is selectively filtered and analyzed according to convenience, the thesis to defend (in an inverted process, in which the conclusion precedes the analysis), or the personal and ideological biases of those researching.
At Reglab, we look for systematic, replicable and transparent ways to do this analysis. To do this, we communicate with consolidated methods in other disciplines and select them according to the body of data and objectives. Examples include:
Statistical analysis
I have quantitative and qualitative data and want to explore a phenomenon based on correlations and trends Qualitative analysis of numerical or large-scale data to identify patterns or correlations
Social costs & benefits analysis
I have quantitative and qualitative data, I want to study the impact of a policy in a broad way Evaluate
the overall impact of a project or policy, considering all social and social costs and benefits
economic (tangible and intangible), including externalities (e.g. fundamental rights).
Regulatory impact analysis
I have quantitative and qualitative data, and I want to study the specific impact of a policy on those affected. Examine the specific effects of a proposed regulation, focusing on feasibility and direct consequences for regulated agents. In general, it does not assess externalities or indirect impacts on other actors.
Content analysis
I have qualitative data, and I want to describe it from text mapping Used to examine large volumes of textual data, such as documents, reports or media, to identify the frequency of words, concepts or categories and formulate hypotheses.
Stakeholder analysis
I have qualified data, and I want to describe it based on stakeholder mapping Ideal for mapping interests and power of influence
of social groups in a process, seeking to identify consensus and conflicts on strategic themes.
Thematic analysis
I have qualitative data, and I want to interpret it through the exploration of emerging themes. Systematic examination of qualitative data (generally subjective), with the grouping of codes into macro categories (themes), identifying emerging topics.
Discourse analysis
I have qualitative data, and I want to interpret it based on the language used. Examines how language and its multimedia expressions construct meanings and shape social reality. Focuses on the relationships and interests implicit in communications.
Do you want to map patterns in texts?
Are you exploring the language used?
Are you exploring emerging themes?
Do you want to map stakeholders?
Do you want to explore correlations and trends?
Are you evaluating specific regulations?
Are you assessing broad economic and social impact?
Do you want to interpret?
Do you want to describe?
Do you want to study the impact of a policy or program?
Procedures for Reducing Bias
Let’s be honest: all research work has biases. We can try to avoid them as much as possible, but it is difficult to eliminate them.
They can be conscious or unconscious, arising from methodological choices, data interpretation or human limitations. And that’s why we consider transparency essential
including the existence of our biases
– which makes interpretation easier and shows a more honest and professional approach than simply hiding them.
This does not mean that we should stop trying to reduce the impact of bias on research results. On the contrary.
Reduction procedures are essential in our work, reinforcing our commitment to the credibility of our analyses.
To this end, we carry out training so that each person recognizes and questions their biases, reflecting on neutrality and
impartiality. Depending on the research structure, one or more reduction methods can be adopted:
Triangulation of Methods: combines different collection techniques (interviews, observations, document analysis) to compare and validate information.
References
Consolidated Theoretical-Methodological:
Whenever possible, we use methods already established in other works and recognized by the academic community.
Participant Review:
presents preliminary results to participants to confirm
whether the interpretations reflect your experiences or opinions.
Open Categorization:
useful for inductive research, it allows categories to emerge from data without imposing prior concepts, minimizing interpretative biases.
Adoption of Predefined Criteria:
For deductive research, the criteria are established before the start of the
classification. The criteria are only adjusted if the categories are insufficient.
Double Validation:
two or more people analyze qualitative data or subjective steps.
Scientific Panel:
One or more external researchers are hired to review the process before, during, or after data analysis.
Record of the coding process:
During encoding, we keep detailed records of all file versions, preserving history and enabling systematic verification.
How do we ensure transparency about our methods?
Although the discussion about methodological rigor exists in academia – and has grown in applied social sciences, such as Law -, there is a growing discussion about how to make this process transparent. The academic community debates not only the importance of methodological transparency, but also
the best ways to document and communicate it effectively.
In addition to transparency, there is a relevant debate about how to ensure standardization that offers clear and consistent references. This standardization is essential to guarantee the replicability of research, allowing other researchers to verify, validate and build on the results presented, which strengthens the credibility of the work.
This movement has gained strength in several areas of knowledge and is discussed in high-impact publications. Journals such as Nature, Science and the Journal of Communication have established rigorous guidelines to ensure replicability, standardization and methodological transparency.
In our work, we adopt two standard practices to meet these criteria: a detailed direction section for future studies and our methodology table.
Directions for Future Studies
No theory or study is definitive. There is no universal theory that explains all phenomena. Every study reflects a specific focus
of reality, and must recognize its limitations and the possibility of other interpretations.
The mandatory nature of this section reflects a fundamental research exercise: critical reflection on its limitations
methodological. This process demonstrates academic maturity and promotes a collaborative space for other researchers to continue the work, whether to validate or question the results through new methods and perspectives.
This approach reinforces Reglab’s role as athink tank that transcends the business function
and consultancy, actively participating in the construction of practical and relevant solutions to contemporary challenges.
This section is mandatory for all Reglab search formats, except Special Formats.
Methodology Annex
At Reglab, we adopt a standardized structure of “methodology annex” for our main studies. This approach is more than a technical choice: it is a practice that reflects our commitment to clarity
and replicability.
Uniformity seeks to make our reports more accessible to frequent readers, such as companies, regulators and journalists. With a predictable structure, the public knows where to find the necessary information, increasing engagement and the usefulness of studies.
Standardization also helps to avoid methodological inconsistencies, ensuring that all relevant aspects are covered in each study. When there is a clear structure to be followed, items such as ethical criteria, limitations of the
study and analytical tools are not neglected.
Our methodology annexes are mandatory for studies from the Radar, Policy Brief and Essays series. For Discussion Papers and Special Formats, the attachment format is not
mandatory, as it may be unnecessary at that stage of the work or incompatible with its nature. Already
for the series Context,the annex is not used due to the reduced scope of the work, but the rigor in references is maintained, with explanations in notes when necessary.
Elements of the Methodology Annex
The Reglab standardized methodology annex must include:
Other Information: Other Technical Limitations: in addition to the limitations and reservations already presented, this section must include, if applicable, limitations related to temporal scope, external sources of data collection or analysis, among others. Research Ethics: in this section, any direct financing and the role of the funding entity in the research must be presented. Authors must also declare respect for the following ethical principles: (i) respect for privacy and confidentiality, (ii) responsible use of public data, (iii) methodological transparency, and (iv) non-discrimination and respect for diversity. Protection of Personal Data: if the research involves direct collection of personal data, it is necessary to clarify the methodological precautions taken to respect applicable legislation, including the General Data Protection Law. Use of Software: all technology tools used in the research must be described, including how they were used.17
Title of the work, authors, research question and summary of the methodology, including structure and research approaches.
Data Collection:
Collection method, sample selection, collection period and reservations.
Data Analysis:
Analysis method, classification categories, coding path (if applicable), analysis period and caveats.
Procedures for Reducing Bias:
description of the procedures used.
Conclusion:
At Reglab, our methodological choices reflect our mission to elevate the discussion of public policies in Brazil. It’s not just about meeting academic or institutional expectations, but ensuring that our work has a real and sustainable impact.
We want to ensure that our work is a useful and impactful tool for everyone facing the regulatory challenges of the media and technology sector. The more people understand our choices, criticize and suggest improvements, the more we will promote a constructive dialogue between different stakeholders, stimulating collaborations that can lead to new perspectives and advances.
We believe that a productive discussion about a work should not be based on opinions or superficial questioning of the results, but on a critical examination of the methods and their application.
This is only possible with transparency and clarity about our research.