Amélie ArtisLecturer in Economics at Sciences Po Grenoble and at the Pacte laboratory
How would you define objectivity in the social sciences?
Objectivity in the social sciences represents the navigator's course: a goal to be reached and a means of surpassing oneself. If we go back to the definition, objectivity implies independence between the thinking subject and the object studied, a faithful representation of the phenomena observed, and impartiality. But the thinking subject chooses his or her object according to multiple criteria and representations, which are social constructs influenced by the life course of individuals, by theories and by institutional structures. It's a tension that's part and parcel of research, and one that the researcher has to find a balance between.
Objectivity, then, is a process that guides and accompanies the researcher throughout the course of his research, and takes shape in several ways. Firstly, it involves distancing oneself from one's subject so as to avoid a militant stance and conflicts of interest. This is crucial if we are to maintain the boundaries between academic and self-interested research. Secondly, objectivity is intended to nurture the researcher's doubt and critical spirit, which is a cornerstone of his ethics and deontology. Lastly, objectivity is designed to foster dialogue by enabling the reproducibility and comparability of research results.
Is researcher neutrality possible and desirable?
Neutrality is both a professional posture and an ethical principle. As a professional posture, it presupposes skills for the researcher, which are as much methodological knowledge as know-how and interpersonal skills. It also presupposes that the researcher takes a back seat to the individual. Neutrality is not sought for its own sake; it is the foundation of the research profession, shared by the entire professional community and constituting a specific characteristic. Of course, it is also a source of intense and erudite debate within the community.
As an ethical principle, neutrality requires researchers to make their identity and representations explicit, and to make every effort to distance themselves from them. Indeed, the researcher's specific role is to deconstruct preconceived ideas, stereotypes, shortcuts and simplifications in order to enable each and every one of us to better understand, interpret and act. However, neutrality is neither spontaneous nor natural, as it cannot be detached from the person practicing it. Indeed, the researcher is a thinking subject with an identity based on several characteristics such as gender, race, beliefs, education and social background. The researcher is also influenced by his or her life course, representations and environment. In spite of this, the researcher must doubt and consider all theoretical and empirical arguments without judgment or bias. Methods are therefore the means to achieve this neutrality, which is more utopian than real.
How important are methods to you as a researcher?
Methods are the lighthouse for the researcher, enabling him to orient himself, to light his way in the dark, and to stay on course. In the social economy, and in many other human sciences, there is a tradition of so-called participatory methods, and in particular action research. The field of action research is characterized by a plurality of approaches, all of which have in common the need to create links between stakeholders and researchers around a research project. These methods are based on a particular posture and approach, which is still not widely used in economics in France. They are complex to implement, insofar as they profoundly modify the established postures between researchers and stakeholders. For academics, these participatory methods imply challenging the traditional separation between the researcher - the knower - and the actor in the field - the object of research. For actors, on the other hand, they imply a commitment to a scientific approach, i.e., above all, a critical perspective on their day-to-day professional actions.
In the field of the social economy, action research is even part of a singular research tradition in which thought and action are developed jointly, notably to nurture the democratic process driven by the members who play a central role in associative and cooperative organizations in particular. This tradition is embodied in the creation of cooperative colleges, but also in a tradition of research embodied by authors on cooperation who are as much actors as researchers, whether they are statutorily university researchers or actors in the field. More recently, the work of Henri Desroche, a field researcher and theorist of cooperation, has helped to name and qualify cooperative action research.
Today, this tradition underpins a methodological approach to research in the social economy based on a number of ideas. Experience and experimentation form the basis of conceptualization; a diversity of actors, researchers and non-researchers alike, participate in the co-production of knowledge useful for action; experiential knowledge is taken into account and valued, and non-academic "researcher-actors" are recognized; observation of collective action practices involves individuals and communities. Today, this action research is mobilized to observe and analyze alternative phenomena to the dominant economic model, through the study of non-market relationships (e.g. reciprocal or redistributive relationships).
Could you present an example of research, ideally from your own work, to illustrate the issues and tensions surrounding objectivity and neutrality in SHS?
As part of an award-winning research project funded by the French Environment and Energy Management Agency (Ademe), we have been analyzingmulti-stakeholder renewable energy projects. In view of the complexity, singularity and novelty of this subject, we felt it necessary to develop an investigative approach combining several intervention methods. We combined quantitative (questionnaire and database analysis), qualitative (semi-structured interviews) and participatory (participatory action research workshops) empirical methods. This work thus mobilized several data analysis methodologies in a single time-space, bringing together researchers, consultant-researchers and actors, who for several months combined their disciplinary approaches and professional and scientific experience in a complementary way.
We were able to monitor the validity of our research from three angles: internal, external and construct. Internal validity refers to the relevance of the data collected and the plausibility of the resulting explanations: how well do the data collected explain the phenomenon under study? The richness of our protocol, and in particular the qualitative, quantitative and participatory cross-fertilization, enabled us to introduce a large number of variables and factors into the analysis.
External validity represents the robustness of a phenomenon outside the framework of the study: are the results obtained generalizable to other populations and contexts than the one characterizing the observations? What is the predictive value of the observations? This criterion is less well assured, due to the emerging and experimental dimension and the small number of projects in operation to date.
Construct validity defines the extent to which the observations made in the research reflect the theoretical concepts being tested: are the factors as introduced and estimated (empirical actions) a good translation of the concepts they embody? The actors mobilized during the research (team, partners, steering committee, workshop participants, etc.) reflect the composition of the ecosystems of actors in the projects studied. We were also alert to certain survey biases common to most empirical protocols. To begin with, we can mention the declarative biases common to any empirical device: strategic bias, over-evaluation, self-representation and so on. Bias is generated by the interviewer himself, who, in seeking a result, anticipates it and obtains results closer to what he anticipated.
In terms of research, our methods have enabled us to co-construct qualitative and quantitative data processed using mixed methods of analysis, to analyze the systems built and their impact through reflective work, and to produce shared analysis based on recommendations. In terms of operational aspects, we used these methods to understand the cooperative approach; identify the deep-seated brakes and levers; draw up scenarios; equip ourselves with project self-assessment tools; outline an action plan and recommendations; identify criteria for characterizing and differentiating projects; highlight specific regional features (context, emergence, drivers, practices, etc.).