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Qualitative Methods in Migration Research

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• First Online: 04 June 2022

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• Ricard Zapata-Barrero 2 &
• Evren Yalaz 2  

Part of the book series: IMISCOE Research Series ((IMIS))

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The unprecedented demographic transformations due to global human mobility and its multifaceted social, political, and economic consequences in both countries of reception and origin, have motivated an increase of interest in having reliable information and deeper knowledge about migratory patterns and the subsequent accommodation of diversity issues both by policymakers and scholars. This is especially true considering that there is a general consensus that this phenomenon is a long-term trend of our more recent history, and it is featured by being complex and unpredictable while giving rise to a permanent atmosphere of uncertainty. We need methodological tools for increasing the understanding of our basic questions on why people move, why they move to certain countries rather than others, what we can do about forced migrants’ vulnerable situations, and how we can link cohesion and diversity, human rights, and security, and a long list of issues and frameworks that shape migration studies today. To have a universal toolkit for producing knowledge is almost a naive request. What we have learned after several decades of research is that migration research needs to be sited and contextualised (King, 2018), and always placed within a given process (Zapata-Barrero, 2018). Most migration-related problems have to do with how people perceive them and behave accordingly, rather than having objective value-free understandings. In other words, migration research is mostly about interpretations rather than facts . Hence, there is an importance to digging into a methodological technique that has a particular role in producing knowledge by analysing how people, institutions, and governments interpret human mobility and diversity dynamics.

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Introduction: Preparing the Way for Qualitative Research in Migration Studies

Mapping the qualitative migration research in europe: an exploratory analysis.

Qualitative and Quantitative Methods as Applied to International Migration

The unprecedented demographic transformations due to global human mobility and its multifaceted social, political, and economic consequences in both countries of reception and origin, have motivated an increase of interest in having reliable information and deeper knowledge about migratory patterns and the subsequent accommodation of diversity issues both by policymakers and scholars. This is especially true considering that there is a general consensus that this phenomenon is a long-term trend of our more recent history, and it is featured by being complex and unpredictable while giving rise to a permanent atmosphere of uncertainty. We need methodological tools for increasing the understanding of our basic questions on why people move, why they move to certain countries rather than others, what we can do about forced migrants’ vulnerable situations, and how we can link cohesion and diversity, human rights, and security, and a long list of issues and frameworks that shape migration studies today. To have a universal toolkit for producing knowledge is almost a naive request. What we have learned after several decades of research is that migration research needs to be sited and contextualised (King, 2018 ), and always placed within a given process (Zapata-Barrero, 2018 ). Most migration-related problems have to do with how people perceive them and behave accordingly, rather than having objective value-free understandings. In other words, migration research is mostly about interpretations rather than facts . Hence, there is an importance to digging into a methodological technique that has a particular role in producing knowledge by analysing how people, institutions, and governments interpret human mobility and diversity dynamics.

The use of qualitative research (QR) is one of the key imprints of how migration research has been developed over recent decades (Yalaz & Zapata-Barrero, 2018 ). The prominence of qualitative research in the research database of the Migration Research Hub makes this trend clear. This interpretative turn is currently providing a growing set of studies based on fieldwork, case, and multi-sited studies, that provides us with mainstreaming patterns and evidence that are driving the development of the migration research field and inform policy and social decision makers.

But what are QR’s main pillars? First, it provides us with a series of techniques to explore in detail how people, organisations, and structures shape the reality where they exist and how far all the reality is conceptually mediated. This approach is often labelled as constructivist, because it focuses on understanding how people/organisations/structures construct the environment and how, at the same time, the environment shapes their perceptions. The premise is always that the migration environment, policies, narratives, and practices, cannot be viewed as external value-free facts, but always as a reality that has been politically and socially constructed. Hence the importance of having a set of methods to deconstruct these cognitive processes and take for granted that migration-related challenges and conflicts are outcomes of a multiplicity of interpretations that often enter into tension and are viewed as irreconcilable. To understand a conflict is to assume that behind a conflict there is always a web of interpretations, a web of concepts, and a web of particular contextual circumstances which need to be inferred through the use of qualitative techniques (Zapata-Barrero, 2018 ) . This heuristic process of “interpreting interpretations”, of understanding the reality, rather than only explaining it, pose several epistemological challenges that the research needs to raise for the sake of producing reliable information and knowledge. We also need to identify the distinctive features and ethical issues that the researcher may encounter in drawing the research design and implementing it. Given the brevity of this chapter, our aim is to provide what we consider to be the nuts and bolts of carrying out QR in migration studies.

1 Raising Epistemological Awareness in Qualitative Research and Its Relevance for Migration Studies

Raising awareness of epistemological questions is key before and during the process of QR. The way we deal with these questions will have an impact on the quality of information and knowledge that the researcher will collect and produce, the potential to convince the large public in general, and the academic community in particular. If we roughly define epistemology as the second-order reflection on the different ways one generates knowledge, including questions of who produces it and how we communicate it, as well as how we ensure the impact of this knowledge, and also who can benefit from it, become straightforward questions one needs to answer from the very beginning. Given that qualitative research deals with subjectivities and perceptions of people/organisations/structures, pre-conceptions, and assumptions behind most of individual behaviors, institutional practices and policies, these epistemological questions become even more consubstantial to filter the fluidity of information one has to deal with, and discriminate its meaningfulness given the research question guiding his/her research.

The first key epistemological challenges are related to objectivity of information collected and knowledge produced, and how to ensure that the same researcher takes a necessary distance from its object of study and prevents the potential influence he/she can have when selecting and categorising information. These are the key issues behind the required self-positionality and self-reflectivity. The way one is related to sources of information is also a key epistemological issue, as well as the way the same researcher views migration studies as a research area capable of influencing reality.

As QR deals with perceptions, interpretations, subjectivities, and opinions, how to ensure the objectivity of findings in carrying out QR in migration studies is one of the key epistemological challenges. QR works then with a different understanding of objectivity in comparison with quantitative analysis. Objectivity in qualitative research is a great challenge, since instead of following the routes of quantity of collecting information, it combines this with quality of differentiated information required. Iosifides ( 2018 ) insists, for instance, that objectivity must always be seen in intersubjective terms, that is, it contains the plurality of differentiated subjective views of a given fact. Technically speaking, objectivity is linked with saturation of information, or the fact that we ensure that we have identified the differentiated variety of information on a given perception of a fact or a process. In other words, for more application to the same technique to different persons/institutions, we will not produce new and differentiated information. When we assume this circle is closed, then we have not only saturated the information, but we can say that the information collected is objective. This saturation technique is one distinctive feature of sampling in qualitative research (Barglowski, 2018 ) and it is used by researchers not only as an indicator of quality (Guest et al., 2006 ), but also as a technique that hampers content validity (Fusch & Ness, 2015 ). Once collected, a process of categorisation and content analysis takes place, namely a process of knowledge production. At this second stage, objectivity requires here the techniques of research that will be introduced in the next section.

The current migratory scenario also stimulates humanitarian engagements and heightens the need to consider your own positionality and reflexivity. The concept of self-positionality helps us to directly address questions about the place of the migration researcher and their relations with the object of study. It invites the researcher, as a social scientist, to view him/her-self in the immediate external and internal surroundings of the object being researched. The neutrality, impartiality and/or involvement in the future of the participants are directly addressed. Self-positionality is a researcher’s attitude inviting researchers to analyse its own system of assumptions and pre-judgements, cultural and ideological assets, convention and norms framework that may interfere in the research process. Even if it is assumed that a complete abstraction of oneself is difficult, even humanly impossible, since the decision to interpret or not to interpret is not open to human beings (Ball, 1995 , p. 7), an effort is required to ensure distance from the values and web of knowledge surrounding the same participant. Self-positionality requires social, political, and cultural distancing and it is always preferable that the research does not belong to the same micro-environment as the participant. In this self-positionality process, migration researchers face various dilemmas about how to position themselves during their fieldwork. This includes questions of social class, but also, depending on the topic under research, can raise questions related to ethnicity, religion, ideology, gender, and so forth. For instance, can a researcher work on its same ethnic background? This highly debated insider/outsider dilemma raises elastic questions of how much disconnection is necessary for a scientific observation and how much participation is needed to approach the phenomenon under study (Iosifides, 2018 ; Carling et al., 2014 ; Pustulka et al., 2019 ). The dividing line between separation and participation and engagement is not a universal matter, but always depends on the contextual needs of the same researcher, given their guiding question. These positionality questions lead us towards reflexivity. Therefore, it is important that researchers develop a critical self-reflexivity and be aware of how their own positionality may take complex and contradictory forms.

Self-Reflexivity is a complementary angle that qualitative migration research needs to address. It helps to ensure we have a holistic perception of the object under our analytical scrutiny and even it allows us to broaden zoom of the same methodological process (these epistemological issues can be viewed as reflexivity thinking). It is sometimes better expressed as a mirror effect to how the researcher is conducting his/her study (Denzin & Lincoln, 2008 ; Lofland et al., 2006 ; Alvesson & Sköldberg, 2012 ). It is often viewed as a “check point” in the research, involving that neither the role of the researcher nor that of the participants can be assumed (Fedyuk & Zentai, 2018 , p. 181).

One of the assets of these second-order thinking requirements is that during all the stages of the research process it generates critical-thinking towards the information being collected, the conditions under which this information was collected and it may include the same influence of the researcher. For articulating self-reflexivity, it is often advisable to keep a research diary, where one take notes of all the circumstances when applying QR techniques. This can be a valuable reference framework to later interpret this information. Self-reflexivity helps the researcher avoid pre-judgements and influences of cultural and conventional systems on the same interpretative process. It also always help to keep an epistemological radar alert on how the same collection and interpretation of information can be socially and political influenced by the researchers own environment.

Combining self-positionality and self-reflexivity carry on necessarily a critical conscience (Aluwihare-Samaranayake, 2012 ) and have a situational stance and connect the research towards perspectivism, which necessarily invites the researcher towards a permanent self-criticism about how oneself conducts the research. It also produces reflections on the same social-class and power positions of the same researcher, which may influence the hermeneutic task of “interpreting the interpretations of others”.

This same combination of self-positionality and self-reflexivity can be made to the same way scholars in general are conducting research and producing knowledge on migration. Exploring questions on how knowledge is produced, who benefits from this knowledge, Footnote 1 and why the same facts may have differentiated centres of knowledge production. Further, we can even also wonder why some knowledge is hidden or why it circulates through parallel routes from the mainstream. Footnote 2 Issues such as the gap between knowledge and politics/policies, or the fact that there may be a “ political use of knowledge ” (Boswell, 2009 ), may also belong to these two second-order thoughts but made on behalf of migration studies. Following this path, eurocentrism and postcolonialism may nurture a debate, but also contested discussions about what is true information and fake migration related news. How migration-related knowledge circulates and influences perceptions and interpretations of the realities of migration is also a necessary epistemological exercise for migrant scholars. Finally, but not least substantial, this epistemological awareness applied to the same migration studies may allow us to enter in current evidence-based policy debates (Baldwin-Edwards et al., 2019 ) or the claim that we need to close the gap between knowledge and policies . In the last resort, struggling against these epistemological challenges may also help the researcher to avoid generalisations and oversimplifications on migration issues, so often followed by citizens and politicians.

2 Designing Qualitative Migration Research (QMR)

Designing qualitative research is best understood through a “process-oriented perspective” (Flick, 2009 , p. 4). While traditional quantitative designs tend to have a linear logic, where stages of research questions, hypotheses, theoretical frameworks, empirical data collection, verification, interpretation, and conclusion can follow each other consecutively and relatively independent of each other, this is rarely the case in qualitative research. The stages of qualitative research often move in a circular way, which makes the researchers reflect on the whole process at each stage. This circular logic can be frustrating since none of the research steps are truly complete until the end of the research process. The circular research process has another dimension for migration researchers. Migration is a dynamic phenomenon. Forms and volumes of mobility, socio-political context of sending and receiving countries, public debates around migration, perceived problems, and reactions change rapidly. Countries like Ireland, Spain and Italy that were once sending are now countries of immigration. Diverse and fragmented flows pose real challenges to academics that strive to explore contemporary migration (Borkert et al., 2006 ). Considering how time-intensive most qualitative research is, it is often the case that what is being studied changes along with the research process. Therefore, migration researchers, not only revise their initial ideas and assumptions during the circular research process, but also reflect on the very dynamic nature of the phenomenon under study.

Qualitative research process involves active decision making at all stages. Starting with deciding the main purpose of the study, it keeps on with formulating the research questions that serve best to the main research objective, choosing the theoretical framework that defines the main assumptions and concepts, defining the empirical data collection strategy, deciding how to access the field, which specific data collection methods to use, whom/what to include in the sample, and when to stop the data collection process and start with the analysis. As the research progresses, revising and refining keep on in a back-and-forth manner. For example, discovery of some new and unexpected findings can make researchers revise, re-formulate, or in some cases change their main questions. Again, it will be the researchers themselves who decide about whether and the extent of which the newly discovered information is relevant to their study and whether and what kind of revisions need to take place in their research design.

There is no magical formula to design good qualitative migration research. However, there are three key questions that must be asked throughout the entire research process:

What is this research about?

Why is it important?

How will it be carried out?

The first question clarifies what you are working on and develops a clear focus. The same migration phenomenon -for example, think about the topics of mobility, integration, or migration policies- can be studied through many different angles focusing on different questions. Therefore, a good qualitative research design starts with a clear purpose, which is focused but not too narrow; flexible enough to accommodate the modifications during the research process; socially, politically, or theoretically relevant that produces useful knowledge; and methodologically feasible that can be studied empirically considering the available resources (Lewis, 2003 ). Research questions that are designed too broadly provide no guidance for the empirical study. On the other hand, too narrow questions hardly contribute to the overall scholarship and can even “block rather than promote new discoveries” (Flick, 2009 , p. 129). For instance, let’s think about the question of whether immigration leads to social conflict. If it is not specified and clarified further, the way it is framed provides little empirical guidance and produces many more questions—such as what type of immigration, in what type of settlement, and what type of conflict—than answers. Moreover, it does not help the research design to flesh out the complex causal mechanism of the migration-conflict nexus. The social reality is often much more tangled than “yes, it does” or “no, it does not” type of answers. So instead of “whether or not” type of questions, asking “when”, “how”, and “why” would provide better guidance for empirical inquiry. Dancygier ( 2010 , p. 3) studies this topic through the questions of: “Why do we observe clashes between immigrants and natives in some locations, but not in others?” and “Why are some immigrant groups likely to become targets of native opposition, while others are more often engaged in conflicts with the state?”. These questions enable the researcher to design a clear empirical strategy that consists of cross-location and cross-group comparisons.

Qualitative research can carry various purposes. Marshall and Rossman ( 2010 ) conceptualise four types of qualitative research purposes: Description to document the researched phenomenon (e.g. what are the characteristics of migratory flows in a specific context? What are the social reactions they provoke? What are the policy responses?); Exploration to discover main categories and generate hypotheses (e.g. what are the salient patterns or categories of migratory flows? How are these flows linked to each other?), Explanation to explain the patterns and to identify plausible relationships (e.g. what is the role of economic scarcity on immigrant/native conflict? In what ways migrants’ economic integration affect their social and political integration?), and Emancipatory purposes to engage in social action (e.g. what are the best practices to minimise social conflict and promote peaceful co-existence?). Multiple purposes can be carried out through the same research. For example, researchers often start with a description before engaging in exploration and explanation. A good research design is the one that clearly identifies the main purposes upfront.

The second question— why is this research important?—makes you to think about the specific contribution that you are making through your research. It asks why others must care about your study. There are various potential ways of contributing. Claiming that your topic is under-explored, or your case study has never been studied before does not by itself justify the importance of your research. Qualitative studies are often well equipped to make contributions by challenging “conventional generalizations and social stereotypes” (Yin, 2010 , p. 221). For instance, qualitative migration research is good at unpacking the category of migrants and examining the crosscutting and intersecting identities. Some examples include King et al. ( 2017 ) that unpack the aging-migration nexus; Runfors ( 2016 ) that empirically shows the problems of the use of “ethnic lens” and brings in the perspectives of racialisation and transnationalism; or Kunz ( 2020 ) that explores the everyday socio-cultural production of the categories of “migrant” and “expatriate”.

Qualitative research is not only good for scrutinising the existing conceptions and theories, it also has a great potential for generating new hypotheses, coining new terms and concepts, and developing new theories. While quantitative research has the comparative advantage for theory testing and verification; the discovery of theory grounded in systematically collected empirical data can be considered as one of the distinctive aspects of qualitative research. In qualitative research, innovative thinking and discovery does not stem from so-called armchair contemplation but takes place in a bottom-up way as researchers collect and work through their data. As Glaser and Strauss ( 2006 , p. 6) put it: “Generating a theory involves a process of research”. Migration Studies is one of the richest fields in terms of generating new theories and concepts. This is mainly because of the close tie of migration research with the research context. For example, Favell ( 2008 ), through his in-depth ethnographic study, coins the terms “Eurostars” and “Eurocities” and explores highly skilled and educated migration in an integrating Europe.

Qualitative research can also make a contribution by calling for action i.e. calling for public policy changes, social justice, and participatory knowledge production. The use of participatory methodologies is quite new in the field of migration studies (Mata-Codesal et al., 2020 ). Through participatory methodologies, researchers take the ethical stance that aims to eliminate hierarchical relations between researchers and participants and recognises the participants as co-producers of knowledge. Participatory research strategies are particularly important when conducting research with vulnerable migrants, where the power discrepancies are starkly pronounced, and the research ethics needs careful considerations.

The third question— how will the research be carried out?—makes researchers conscious of their methodological choices that provide the tools to carry out their research. Research objectives and questions determine which methodological tools are needed to answer them, not the other way around. As Creswell ( 2007 , p. 101) puts it: “(t)he design of a qualitative study begins before the researcher chooses a qualitative approach. It begins by the researcher stating the problem …, formulating the central purpose of the study, and providing the research questions”. That is why the choice of qualitative, quantitative, and mixed-method designs cannot be the starting point of a research process but must be followed by the choice of research objectives and questions.

Migration researchers need to be conscious of how different methodological approaches and tools produce varied understandings of the same phenomenon. For example, Harries et al. ( 2019 ) demonstrates how bringing different methodological tools together (Census statistics, qualitative interviews, document analysis, and historical analysis) enabled them to challenge the ways in which diversity assumes an objective reality and reveal multiple representations of diversity in Cheetham Hill. The Census data provided them with the ethnic composition details of the research site. They could explore the lived experience of different ethnic groups as well as how diversity categories are perceived through the qualitative interviews.

Qualitative research tools are diverse and serve different purposes. One of the key distinctions is made between naturally occurring and generated data (Lewis, 2003 , p. 56). Researchers choose naturally occurring data -such as observation, document analysis, discourse and conversational analysis- when they are interested in exploring the researched phenomenon in its natural context with a minimum intervention. On the other hand, generated data -such as interviews, focus groups, photo elicitation, mental mapping- are produced out of the natural setting for research purposes. While naturally occurring data mainly rely on researchers’ interpretation of what is being studied, participants have a direct opportunity to explain themselves and convey their own interpretation in generated data (Lewis, 2003 , p. 57). Two main types of generated data—individual interviews and focus groups—also play different roles. Individual interviews are good for in-depth exploration of individual accounts. Focus groups, in addition to revealing individual opinions, generate group discussion and provide information on group consensus, conflicts, and interaction (Cyr, 2015 ). While a research design can use multiple data collection tools, it is important to have a good justification for each added method.

Starting a qualitative migration research fieldwork study brings up many questions such as how to gain access to the field e.g. individuals, groups, institutions, organisations under the study; whom to include in the study; how to negotiate researcher’s position in the field; how to build rapport and gain trust while ensuring the ethical conduct. Below, we will address some key issues that migration researchers face while conducting their qualitative fieldwork and discuss their research ethics implications.

Entering the field : Gaining access to the research site and participants can be particularly challenging for migration scholars, because they might be working on a group of people who are mobile and hard to track down; undocumented and not visible in local registries; and/or are vulnerable in different ways that their research participation needs to be supported rather than assumed. It is a common practice to gain access though gatekeepers (like community leaders) and key participants. Yet, migration researchers need to be aware of potential consequences of gaining access in such ways e.g. disabling the participation of certain groups or receiving biased answers influenced by the gatekeepers.

Sampling : One of the key differences between qualitative and quantitative research designs lies on their logic of sampling. Statistical research aims to make inferences about a larger population through a smaller sample. Therefore, having a sample as representative as possible is a key issue in statistics. Drawing a larger sample and using random sampling strategies when possible are useful practices in this sense. However, qualitative research has quite a different sampling logic. In qualitative research, relevant questions are “which cases?” rather than “how many?” (Flick, 2009 , p. 31) and what these cases represent i.e. what they are “a case of” (Gerring, 2007 ). Therefore, qualitative research includes sampling strategies such as theoretical sampling where emerging theory determines what cases to select (Glaser & Strauss, 2006 ) or purposive sampling where certain cases are selected because of their specific qualities such as extreme, deviant, typical cases (Patton, 2002 ). Many young researchers and students ask the question of “how many cases do I need for my qualitative study to be scientific?” (see Small, 2009 ). There is often a common belief that the more cases we study the more representative our research is. However, as Bloemraad ( 2013 ) rightly points out that interviewing 50 immigrants instead of 40 is not inherently good, unless these 10 additional participants represent a particular category or experience that is not already covered by the first 40 interviews. In qualitative research, it is a common practice to stop adding new cases once the “theoretical saturation” is achieved i.e. nothing new emerges with additional cases (Flick, 2009 , p. 138).

Research ethics : As institutional ethical regulations expand in social science research, there is an increasing call for field-specific and method-sensitive ethical considerations that address particular ethical issues faced by qualitative migration researchers (Zapata-Barrero & Yalaz, 2020 ; Ullah et al., 2020 ). The ethical guidelines that every research must follow include respect for participants’ autonomy i.e. ensuring voluntary participation, informed consent, confidentiality and anonymity; responsibility to identifiable benefits ( beneficence ); responsibility to avoid harm ( nonmaleficence ); and equal treatment of participants ( justice ) (Murphy & Dingwall, 2001 ). Yet, these abstract principles are too general to address the emerging ethical issues in day-to-day research practices especially in the field of migration. Migrants, refugees, and asylum seekers often suffer from varied sources of vulnerability and need particular ethical safeguards that are sensitive to the research context. Blindly following the formal codes may not provide real protection to these vulnerable participants and may even increase the risk of harm.

Dissemination of research findings : Qualitative research poses specific challenges in presenting their findings, since their data often includes narratives of the participants (Yin, 2010 ). Researchers need to decide what to quote, how long, when to include direct and indirect quotes, and how to include non-verbal cues. In-depth and detailed analysis of small number of cases brings up the issue of how to protect confidentiality and anonymity of the participants. While using pseudonyms is one option, it does not fully guarantee anonymity. Some findings, despite their importance and relevance, might need to be left out, if they include sensitive information that can be traced back to the participants and put them in risk. Migration research directly shapes public debates, controversies, and policymaking. Therefore, each decision at the dissemination stage -what and how to disseminate- needs to consider that it will have important and real consequences on migrants’ lives.

3 Conclusion

QR has always been at the heart of migration studies. Yet, the systematic attention to methodological issues in migration studies is relatively new (Zapata-Barrero & Yalaz, 2018 ). Studying migrants and migration-related phenomena has its own methodological challenges. While not all migrants are vulnerable, QR has an important role in exploring the lived experiences of migrants who live at the margins of their societies, informing the policymakers and stakeholders about the causes and consequences of such vulnerabilities and calling for action to change. The multi-faceted and unbounded nature of the migration phenomenon, challenges traditional research practices and requires cross-national, transnational, and inter-disciplinary methodological perspectives. Qualitative migration researchers have a key role in demonstrating the constructed nature of the categories such as ‘migrant’, ‘undocumented’, ‘citizen’, ‘border’ and so on. Even though these categories are socially and politically produced, they have real material effects on how states and societies are organised. QR, through a bottom-up knowledge production process, has a distinctive advantage in exploring how these constructed migration categories are perceived and experienced in the everyday life of individuals, organisations, and institutions. Last but not least, qualitative migration researchers must pay attention to recent calls for democratising qualitative research methods (Edwards & Brannelly, 2017 ). Inclusive, participatory, and emancipatory research practices not only aim to ensure research ethics, but also fundamentally transform the nature of knowledge-production in terms of “what counts as knowledge and who produces, owns, uses and benefits from it, with implications beyond that for wider social relations” (Edwards & Brannelly, 2017 , p. 272). Avoiding traditional hierarchies between researchers and participants and recognising migrants as co-producers of migration knowledge will be an important step toward democratising migration research and its methodological tools.

The question of who may potentially benefit from the knowledge produced is an important ethical enquiry (Zapata-Barrero & Yalaz, 2020 ).

The role knowledge plays at the level of migration politics, policies and actors involved is well addressed by Boswell ( 2009 ).

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Introducing Phi-3: Redefining what’s possible with SLMs

By Misha Bilenko Corporate Vice President, Microsoft GenAI

Posted on April 23, 2024 4 min read

• Tag: Copilot
• Tag: Generative AI

We are excited to introduce Phi-3, a family of open AI models developed by Microsoft. Phi-3 models are the most capable and cost-effective small language models (SLMs) available, outperforming models of the same size and next size up across a variety of language, reasoning, coding, and math benchmarks. This release expands the selection of high-quality models for customers, offering more practical choices as they compose and build generative AI applications.

Starting today, Phi-3-mini , a 3.8B language model is available on Microsoft Azure AI Studio , Hugging Face , and Ollama . 

• Phi-3-mini is available in two context-length variants—4K and 128K tokens. It is the first model in its class to support a context window of up to 128K tokens, with little impact on quality.
• It is instruction-tuned, meaning that it’s trained to follow different types of instructions reflecting how people normally communicate. This ensures the model is ready to use out-of-the-box.
• It is available on Azure AI to take advantage of the deploy-eval-finetune toolchain, and is available on Ollama for developers to run locally on their laptops.
• It has been optimized for ONNX Runtime with support for Windows DirectML along with cross-platform support across graphics processing unit (GPU), CPU, and even mobile hardware.
• It is also available as an NVIDIA NIM microservice with a standard API interface that can be deployed anywhere. And has been optimized for NVIDIA GPUs . 

In the coming weeks, additional models will be added to Phi-3 family to offer customers even more flexibility across the quality-cost curve. Phi-3-small (7B) and Phi-3-medium (14B) will be available in the Azure AI model catalog and other model gardens shortly.   

Microsoft continues to offer the best models across the quality-cost curve and today’s Phi-3 release expands the selection of models with state-of-the-art small models.

Azure AI Studio

Phi-3-mini is now available

Groundbreaking performance at a small size

Phi-3 models significantly outperform language models of the same and larger sizes on key benchmarks (see benchmark numbers below, higher is better). Phi-3-mini does better than models twice its size, and Phi-3-small and Phi-3-medium outperform much larger models, including GPT-3.5T.  

All reported numbers are produced with the same pipeline to ensure that the numbers are comparable. As a result, these numbers may differ from other published numbers due to slight differences in the evaluation methodology. More details on benchmarks are provided in our technical paper . 

Note: Phi-3 models do not perform as well on factual knowledge benchmarks (such as TriviaQA) as the smaller model size results in less capacity to retain facts.  

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Responsible ai principles

Phi-3 models were developed in accordance with the Microsoft Responsible AI Standard , which is a company-wide set of requirements based on the following six principles: accountability, transparency, fairness, reliability and safety, privacy and security, and inclusiveness. Phi-3 models underwent rigorous safety measurement and evaluation, red-teaming, sensitive use review, and adherence to security guidance to help ensure that these models are responsibly developed, tested, and deployed in alignment with Microsoft’s standards and best practices.  

Building on our prior work with Phi models (“ Textbooks Are All You Need ”), Phi-3 models are also trained using high-quality data. They were further improved with extensive safety post-training, including reinforcement learning from human feedback (RLHF), automated testing and evaluations across dozens of harm categories, and manual red-teaming. Our approach to safety training and evaluations are detailed in our technical paper , and we outline recommended uses and limitations in the model cards. See the model card collection .  

Unlocking new capabilities

Microsoft’s experience shipping copilots and enabling customers to transform their businesses with generative AI using Azure AI has highlighted the growing need for different-size models across the quality-cost curve for different tasks. Small language models, like Phi-3, are especially great for: 

• Resource constrained environments including on-device and offline inference scenarios.
• Latency bound scenarios where fast response times are critical.
• Cost constrained use cases, particularly those with simpler tasks.

For more on small language models, see our Microsoft Source Blog .

Thanks to their smaller size, Phi-3 models can be used in compute-limited inference environments. Phi-3-mini, in particular, can be used on-device, especially when further optimized with ONNX Runtime for cross-platform availability. The smaller size of Phi-3 models also makes fine-tuning or customization easier and more affordable. In addition, their lower computational needs make them a lower cost option with much better latency. The longer context window enables taking in and reasoning over large text content—documents, web pages, code, and more. Phi-3-mini demonstrates strong reasoning and logic capabilities, making it a good candidate for analytical tasks. 

Customers are already building solutions with Phi-3. One example where Phi-3 is already demonstrating value is in agriculture, where internet might not be readily accessible. Powerful small models like Phi-3 along with Microsoft copilot templates are available to farmers at the point of need and provide the additional benefit of running at reduced cost, making AI technologies even more accessible.  

ITC, a leading business conglomerate based in India, is leveraging Phi-3 as part of their continued collaboration with Microsoft on the copilot for Krishi Mitra, a farmer-facing app that reaches over a million farmers.

“ Our goal with the Krishi Mitra copilot is to improve efficiency while maintaining the accuracy of a large language model. We are excited to partner with Microsoft on using fine-tuned versions of Phi-3 to meet both our goals—efficiency and accuracy! ”    Saif Naik, Head of Technology, ITCMAARS

Originating in Microsoft Research, Phi models have been broadly used, with Phi-2 downloaded over 2 million times. The Phi series of models have achieved remarkable performance with strategic data curation and innovative scaling. Starting with Phi-1, a model used for Python coding, to Phi-1.5, enhancing reasoning and understanding, and then to Phi-2, a 2.7 billion-parameter model outperforming those up to 25 times its size in language comprehension. 1 Each iteration has leveraged high-quality training data and knowledge transfer techniques to challenge conventional scaling laws. 

Get started today

To experience Phi-3 for yourself, start with playing with the model on Azure AI Playground . You can also find the model on the Hugging Chat playground . Start building with and customizing Phi-3 for your scenarios using the  Azure AI Studio . Join us to learn more about Phi-3 during a special  live stream of the AI Show.  

1 Microsoft Research Blog, Phi-2: The surprising power of small language models, December 12, 2023 .

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Studies on the Value of Data

The U.S. Bureau of Economic Analysis has undertaken a series of studies that present methods for quantifying the value of simple data that can be differentiated from the complex data created by highly skilled workers that was studied in Calderón and Rassier 2022 . Preliminary studies in this series focus on tax data, individual credit data, and driving data. Additional examples include medical records, educational transcripts, business financial records, customer data, equipment maintenance histories, social media profiles, tourist maps, and many more. If new case studies under this topic are released, they will be added to the listing below.

• Capitalizing Data: Case Studies of Driving Records and Vehicle Insurance Claims | April 2024
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Title: superbubbles as the source of dynamical friction: gas migration, stellar and dark matter contributions.

Abstract: The gas distribution in galaxies is smooth on large scales but is usually inhomogeneous as well as time-dependent on smaller scales. The time-dependence originates from processes such as cloud formation, their collisions and supernovae (SNe) explosions. The inhomogeneities in the matter distribution give rise to variations in the local galactic gravitational potential, which can contribute towards dynamically coupling the gas disk to the stellar and the dark matter (DM) components of the galaxy. Specifically, multiple supernovae occurring in young stellar clusters give rise to superbubbles (SB), which modify the local acceleration field and alter the energy and momentum of stars of DM particles traversing them, in broad analogy to the dynamical friction caused by a massive object. We aim to quantify how the acceleration field from SBs causes dynamical friction and contributes to the secular evolution of galaxies. In order to assess this, we construct the density modifications to the gas distribution that mimics a SB. By evaluating the acceleration field from these density modifications, we see how the momentum or angular momentum of the gas hosting the SBs changes when stars pass through the SB. Combining the effects of all the stars and SBs we, construct an empirical approximation formula for the momentum loss in homogeneous and isotropic cases. We find that the rate at which the gas disc loses its specific angular momentum via the above process is up to 4% per Gyr, which translates to under half of its original value over the lifetime of the disc. Finally, we studied how the dynamical coupling of the gas disk with the DM halo depends on assumptions on the halo kinematics (e.g. rotation) and found a ~0.3% variation in the gas disc secular evolution between different DM kinematic models.

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