Critical Ethnography: Uncovering Power, Inequality, and Social Change Through Research

September 29, 2025 by Afza Lal Din

What is Critical Ethnography Uncovering Power, Inequality, and Social Change Through Research. Critical ethnography is a research approach that, like traditional ethnography, uses in-depth, long-term observations but incorporates critical theory to analyze power dynamics, inequality, and social injustice.

The Critical Ethnography: Uncovering Power, Inequality, and Social Change Through Research

It aims to promote the emancipation and social change of marginalized groups. It requires researchers to reflect on their own positionality, question taken-for-granted assumptions, and use their knowledge to advocate for liberation and amplify the voices of the oppressed.

What Is Critical Ethnography?

An emerging branch of ethnography that resonates with the critical paradigm outlined in previous posts is the field of critical ethnography. Here not only is qualitative, anthropological, participant, observer-based research undertaken, but its theoretical basis lies in critical theory (Quantz, 1992:448; Carspecken, 1996). As was outlined in previous posts, this paradigm is concerned with the exposure of oppression and in equality in society with a view to emancipating individuals and groups towards collective empowerment. In this respect research is an inherently political enterprise.

Core Principles That Define Critical Ethnography

Carspecken (1996, 4ff.) suggests several key premises of critical ethnography:

Power and Knowledge

Research and thinking are mediated by power relations;
These power relations are socially and historically located;
Facts and values are inseparable;

Social Dynamics and Language

Relationships between objects and concepts are fluid and mediated by the social relations of production;
Language is central to perception;
Certain groups in society exert more power than others;

Systems of Oppression

Inequality and oppression are inherent in capitalist relations of production and consumption;
Ideological domination is strongest when oppressed groups see their situation as inevitable, natural or necessary;
Forms of oppression mediate each other and must be considered together (e.g. Race, gen der, class).

The Political Nature of Critical Ethnographic Research

Quantz (1992:473–4) argues that research is inescapably value-laden in that it serves some interests, and that in critical ethnography the task of researchers is to expose these interests and move participants towards emancipation and freedom. The focus and process of research are thus political at heart, concerning issues of power, domination, voice and empowerment. In critical ethnography the cultures, groups and individuals being studied are located in con texts of power and interests. These contexts have to be exposed, their legitimacy interrogated, and the value base of the research itself exposed.

Reflexivity and Legitimacy

Reflexivity is high in critical ethnography. What separates critical ethnography from other forms of ethnography is that, in the former, questions of legitimacy, power, values in society and domination and oppression are fore-grounded.

How does the critical ethnographer proceed?

The Five-Stage Process of Critical Ethnography

Carspecken and Apple (1992:512–14) and Carspecken (1996:41–2) identify five stages in critical ethnography:

Stage 1: compiling the primary record through the collection of mono-logical data

Objectives

At this stage the researcher is comparatively passive and unobtrusive—a participant observer. The task here is to acquire objective data and it is ‘mono-logical’ in the sense that it concerns only the researcher writing her own notes to herself.

Key Validity Checks

Lincoln and Guba (1985) suggest that validity checks at this stage will include:

Using multiple devices for recording together with multiple observers;
Using a flexible observation schedule in or der to minimize biases;
Remaining in the situation for a long time in order to overcome the Hawthorne effect;
Using low-inference terminology and descriptions;
Using peer-debriefing;
Using respondent validation. Echoing Habermas’s (1979, 1982, 1984) work on validity claims, validity here includes truth (the veracity of the utterance), legitimacy (rightness and appropriateness of the speaker), comprehensibility (that the utterance is comprehensible) and sincerity (of the speaker’s intentions).

Carspecken (1996:104–5) takes this further in suggesting several categories of reference in objective validity:

(a)That the act is comprehensible, socially legitimate and appropriate

(b) That the actor has a particular identity and particular intentions or feelings when the action takes place

(c) That objective, contextual factors are acknowledged.

Stage 2: preliminary reconstructive analysis

Objectives

Reconstructive analysis attempts to uncover the taken-for-granted components of meaning or abstractions that participants have of a situation. Such analysis is intended to identify the value systems, norms, key concepts that are guiding and underpinning situations. Carspecken (ibid.: 42) suggests that the researcher goes back over the primary record from stage one to ex amine patterns of interaction, power relations, roles, sequences of events, and meanings ac corded to situations.

He asserts that what distinguishes this stage as ‘reconstructive’ is that cultural themes, social and system factors that are not usually articulated by the participants themselves are, in fact, reconstructed and articulated, making the un-discursive into discourse. In moving to higher level abstractions this stage can utilize high level coding.

Validity Strategies

In critical ethnography Carspecken (ibid.: 141) delineates several ways of ensuring validity at this stage:

Use interviews and group discussions with the subjects themselves.
Conduct member checks on the reconstruction in order to equalize power relations.
Use peer debriefing (a peer is asked to review the data to suggest if the researcher is being too selective, e.g. of individuals, of data, of inference) to check biases or absences in re constructions.
Employ prolonged engagement to heighten the researcher’s capacity to assume the insider’s perspective.
Use ‘strip analysis’ checking themes and segments of extracted data with the primary data, for consistency.
Use negative case analysis

Stage 3: dialogical data collection

Here data are generated by, and discussed with, the participants (Carspecken and Apple, 1992). The authors argue that this is not-naturalistic in that the participants are being asked to reflect on their own situations, circumstances and lives and to begin to theorize about their lives. This is a crucial stage because it enables the participants to have a voice, to democratize the research. It may be that this stage produces new data that challenge the preceding two stages.

Quality Assurance Methods:

In introducing greater subjectivity by participants into the research at this stage Carspecken (1996:164–5) proffers several validity checks, for example:

(a) Consistency checks on interviews that have been recorded

(b) Repeated interviews with participants

(d) Avoiding leading questions at interview, reinforced by having peer debriefs check on this

(e) Respondent validation

(f) Asking participants to use their own terms in describing naturalistic contexts, and to explain these terms

Stage 4: discovering system relations

Objectives

This stage relates the group being studied to other factors that impinge on that group, for example, local community groups, local sites that produce cultural products. At this stage Carspecken (ibid.: 202) notes that validity checks will include:

(a) Maintaining the validity requirements of the earlier stages

(b) Seeking a match between the researcher’s analysis and the commentaries that are provided by the participants and other researchers

Stage 5: using system relations to explain findings

Objectives

This stage seeks to examine and explain the findings in light of macro-social theories (ibid.: 202). In part this is a matching exercise, to fit the research findings within a social theory. In critical ethnography, therefore, the move is from describing a situation, to understanding it, to questioning it, and to changing it. This parallels the stages of ideology critique set out in previous posts:

Step 1 A description of the existing situation—a hermeneutic exercise.

Step 2 A penetration of the reasons that brought the situation to the form that it takes.

Step 3 An agenda for altering the situation.

Step 4 An evaluation of the achievement of the new situation.

Technology in Ethnographic Research

LeCompte and Preissle (1993) provide a summary of ways in which information technology can be utilized in supporting ethnographic research (see also Tesch, 1990). As can be seen from the list below, the uses of information technology are diverse; as data have to be processed, and as word data are laborious to process, and as several powerful packages for data analysis and processing exist, researchers will find it useful to make full use of computing facilities.

Data Management and Analysis

These can be used as follows (LeCompte and Preissle, 1993:280–1):

To store and check (e.g. proofread) data.
To collate and segment data and to make numerous copies of data.
To enable memoing to take place, together with details of the circumstances in which the memos were written.
To conduct a search for words or phrases in the data and to retrieve text.

Advanced Analysis Capabilities

To attach identification labels to units of text, (e.g. questionnaire responses), so that subsequent sorting can be undertaken.
To partition data into units that has been determined either by the researcher or in response to the natural language itself.
To enable preliminary coding of data to be undertaken.

Data Management and Analysis

To sort, re-sort, collate, classify and reclassify pieces of data to facilitate constant comparison and to refine schemas of classification.
To code memos and bring them into the same schema of classification.
To assemble, re-assemble and recall data into categories.
To undertake frequency counts (e.g. of words, phrases, codes).

Advanced Analysis Capabilities

To cross-check data to see if they can be coded into more than one category, enabling link ages between categories to be discovered.
To establish the incidence of data those are contained in more than one category.
To retrieve coded data segments from subsets (e.g. by sex) in order to compare and contrast data.
To search for pieces of data that appears in a certain (e.g. chronological) sequence.

Popular Software Packages

To establish linkages between coding categories.
To display relationships of categories (e.g. hierarchical, temporal, relational, sub-sumptive, superordinate).
To quote data in the final report.

Kelle (1995) suggests that computers are particularly effective at coping with the often-en countered problem of data overload and retrieval in qualitative research. Computers, it is argued, enable the researcher to use codes, memos, hypertext systems, selective retrieval, cooccurring codes, and to perform quantitative counts of qualitative data types (see also Seidel and Kelle, 1995).

In turn, these authors suggest, this enables linkages of elements to be under taken, the building of networks, and, ultimately, theory generation to be undertaken. Indeed Lonkila (1995) indicates how computers can assist in the generation of grounded theory through coding, constant comparison, linkages, memoing, use of diagrams, verification and, ultimately, theory building.

In this process Kelle and Laurie (1995:27) suggest that computer aided methods can enhance:

(a) Validity (by the management of samples)

(b) Reliability (by retrieving all the data on a given topic, thereby ensuring trustworthiness of the data). A major feature of computer use is in the coding and compilation of data (for example, Kelle (1995:62–104).

Lonkila (1995) identifies several kinds of codes. Open coding generates categories and defines their properties and dimensions. Axial coding works within one category, making connections between subgroups of that category and makes connections between one category and another. This might be in terms of the phenomena that are being studied, the causal conditions that lead to the phenomena, the context of the phenomena and their intervening conditions, and the actions and interactions of, and consequences for, the actors in situations. Selective coding identifies the core categories of text data.

Seidel and Kelle (1995) suggest that codes can denote a text, passage, or fact, and can be used to construct data networks. There are several computer packages for qualitative data (see Kelle, 1995), for example: AQUAD; ATLAS/ti; HyperQuad2; HyperRESEARCH; Hypersoft; Kwaliton; Martin; MAX; WINMAX; NUD.IST; QUALPRO; Textbase Alpha, ETHNOGRAPH, ATLAS.ti, Code-A-Text, Decision Explorer, Diction. Some of these are reviewed by Prein, Kelle and Bird (1995:190–209). To conclude this post we identify a number of difficulties that arise in the implementation of ethnographic and naturalistic research programs.

Some Problems with Ethnographic and Naturalistic Approaches

There are several difficulties in ethnographic and natural approaches. These might affect the reliability and validity of the research, and include:

1 The definition of the situation—the participants are being asked for their definition of the situation, yet they have no monopoly on wisdom. They may be ‘falsely conscious’ (unaware of the ‘real’ situation), deliberately distorting or falsifying information, or highly selective. The issues of reliability and validity here are addressed in previous posts (see the discussions of triangulation).

2 Reactivity (the Hawthorne effect)—the presence of the researcher alters the situation as participants may wish to avoid, impress, direct, deny, influence the researcher. Again, this is discussed in previous posts. Typically the problem of reactivity is addressed by careful negotiation in the field, remaining in the field for a considerable time, ensuring as far as possible a careful presentation of the re searcher’s self.

3 The halo effect—where existing or given information about the situation or participants might be used to be selective in sub sequent data collection, or may bring about a particular reading of a subsequent situation (the research equivalent of the self-fulfilling prophecy). This is an issue of reliability, and can be addressed by the use of a wide, triangulated data base and the assistance of an external observer.

4 The implicit conservatism of the interpretive methodology—the kind of research described in this post, with the possible exception of critical ethnography, accepts the perspective of the participants and corroborates the status quo. It is focused on the past and the present rather than on the future.

5 There is the difficulty of focusing on the familiar—participants (and, maybe researchers too) being so close to the situation that they neglect certain, often tacit, aspects of it. The task, therefore, is to make the familiar strange. Delamont (1981) suggests that this can be done by:

Studying unusual examples of the same issue (e.g. atypical classroom, timetabling or organizations of schools);
Studying examples in other cultures;
Studying other situations that might have a bearing on the situation in hand (e.g. if studying schools it might be useful to look at other similar-but-different organizations, for instance hospitals or prisons);
Taking a significant issue and focusing on it deliberately, e.g. gendered behavior.

6 The open-endedness and diversity of the situations studied. Hammersley and Atkinson (1983) counsel that the drive to wards focusing on specific contexts and situations might overemphasize the difference between contexts and situations rather than their gross similarity, their routine features. Researchers, he argues, should be as aware of regularities as of differences.

7 The neglect of wider social contexts and constraints. In studying situations that emphasize how highly context-bound they are, this might neglect broader currents and con texts—micro-level research risks putting boundaries that exclude important macro level factors. Wider—macro-contexts cannot be ruled out of individual situations.

8 The issue of generalizability. If situations are unique and non-generalizable, as many naturalistic principles would suggest, how is the issue of generalizability going to be addressed? To which contexts will the findings apply, and what is the role and nature of replication studies?

9 How to write up multiple realities and explanations? How will a representative view be reached? What if the researcher sees things that are not seen by the participants?

10 Who owns the data, the report, and who has control over the release of the data?

Naturalistic and ethnographic research, then, are important but problematical research methods in education. Their widespread use signals their increasing acceptance as legitimate and important styles of research.

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