A note on social ontology: for housing studies students

 A note on social ontology: for housing studies students

Highlight 6 main ideas of social ontology in the context of Housing Studies dissertation projects, and then, discuss briefly on the following research philosophies view the topic of social ontology: positivism, interpretivism, pragmatism and critical realism.

Social ontology concerns what kinds of social entities and realities exist, and how they produce outcomes. In Housing Studies, it helps a dissertation move beyond treating housing as merely a physical dwelling or market commodity, and instead analyse it as an institutional, relational, cultural, and political phenomenon.

Six main ideas

1.    Housing is socially constituted
A dwelling has material features, but its meaning as “home,” “investment,” “public housing,” “luxury,” or “inadequate housing” arises through laws, norms, markets, and lived experience. For example, the same flat may be a source of security to an owner, an investment asset to a landlord, and an overcrowded constraint to a tenant.

2.    Social structures are real and consequential
Institutions such as property-rights systems, mortgage markets, housing allocation rules, planning regimes, welfare policy, and landlord–tenant law shape housing opportunities and outcomes. They are not simply individual opinions; they organise and constrain action over time. Housing research using critical realism particularly emphasises property rights, savings and investment systems, labour, and welfare relations as arrangements that influence housing pathways.routledge

3.    Agency matters, but is enabled and constrained
Households, landlords, developers, planners, banks, and governments make choices. However, their choices occur within unequal constraints: income, tenure rules, interest rates, family obligations, discrimination, location, and access to credit. A good dissertation therefore avoids explaining affordability solely as “individual preference” or solely as “structure.”

4.    Housing reality is relational
Housing outcomes emerge from relationships among actors and systems: tenants and landlords, developers and financiers, households and the state, neighbourhoods and transport systems. Housing consumption is linked to the interconnected processes of promotion, finance, construction, management, and use.repository.tudelft

5.    Meanings and identities influence housing action
People do not make housing decisions on price alone. Ideas about family duty, status, security, privacy, home ownership, ageing, or belonging shape tenure preferences and residential choices. These meanings can differ by social class, generation, gender, migration experience, and local culture.

6.    Housing systems are historically contingent and changing
Current housing conditions reflect earlier policies, market institutions, and political decisions. Historical path dependence matters: a policy that initially promoted home ownership, for instance, can produce long-term effects on wealth inequality, intergenerational access, and attitudes towards renting. Critical-realist housing research examines the necessary and contingent conditions that combine to generate observed outcomes.repository.tudelft+1

Philosophical perspectives

Philosophy	Ontological view	Implication for a Housing Studies dissertation
Positivism	There is a single, objective social reality that exists independently of researchers and participants, and can be observed, measured, and tested. repository.up+1	Treats affordability, waiting time, house prices, overcrowding, tenure, or commuting distance as measurable variables. A study might test whether household income, age, or mortgage rates statistically predict home ownership.
Interpretivism	Social reality is multiple, subjective, and socially constructed through people’s meanings, interactions, and contexts. repository.up+1	Investigates how people understand housing. For example: “How do young adults in Hong Kong interpret home ownership, family support, and housing insecurity?” Interviews, observations, and thematic analysis fit well.
Pragmatism	Does not require commitment to one fixed account of reality; it accepts potentially differing ontological assumptions and prioritises the research problem and useful consequences of inquiry. repository.up+1	Suitable for practical, policy-oriented questions. A researcher could combine price and survey data with interviews to ask both how widespread rental stress is and how tenants experience and respond to it.
Critical realism	A real world exists independently of our knowledge, but it is layered, open, and shaped by often unobservable structures and causal mechanisms. Observable events do not reveal all causes. nsuworks.nova+1	Seeks explanation rather than only description or interpretation. For example, rising housing unaffordability may be studied through interacting mechanisms such as land policy, financialisation, credit conditions, welfare arrangements, developer power, and household strategies.

Key distinctions

Positivism asks: What measurable factors predict a housing outcome?
Interpretivism asks: What does housing mean to people, and how do they experience it?
Pragmatism asks: What combination of perspectives and methods best addresses the practical problem?
Critical realism asks: What underlying mechanisms and structural conditions generate the observed outcome, in this particular context?

Dissertation application

For an MBA or Housing Studies dissertation, choose ontology based on your explanatory ambition:

• Use positivism for variable-based studies, hypothesis testing, and generalisable associations.
• Use interpretivism when residents’, tenants’, homebuyers’, or policymakers’ meanings are central.
• Use pragmatism for mixed-methods research focused on producing actionable recommendations.
• Use critical realism when you want to explain why a housing outcome occurs through the interaction of individual agency, institutions, history, and market structures—especially useful for policy and comparative housing research. Critical realism is advocated in housing research because housing phenomena are complex, open, and structured rather than reducible to simple event-outcome relationships.routledge+1

A concise ontology statement for a critical-realist housing dissertation could be:

This study adopts a critical-realist social ontology, viewing housing affordability as a real but socially produced outcome. It is generated through the contingent interaction of household agency with deeper institutional, economic, and policy structures, some of which may not be directly observable.

Two useful references for a dissertation discussion of social ontology—one foundational and one directly applied to Housing Studies—are:

·        Berger, P.L. and Luckmann, T. (1966) The social construction of reality: A treatise in the sociology of knowledge. Garden City, NY: Doubleday. This foundational text supports an interpretivist or social-constructionist account of housing meanings, norms, and institutions.cmc.marmot+1

·        Lawson, J. (2006) Critical realism and housing research. London and New York: Routledge. This is especially relevant to Housing Studies because it develops a critical-realist ontological approach to explaining housing systems and comparative housing outcomes.taylorfrancis+1

In-text citations would be: (Berger and Luckmann, 1966) and (Lawson, 2006).

Lecture note on triangulation: for Housing Studies students

Lecture note on triangulation: for Housing Studies students

In the context of doing a part-Housing Studies dissertation project, please clarify whether using (1) two academic theories and (2) using two primary research methods, to study the same research topic, e.g. to evaluate the experience on residential quality of the Hong Kong Gen z in coliving apartments, are a kind of triangulation? If so, please provide 3 straightforward steps to conduct it in case 1 (related to academic theories) and case 2 (related to research methods).

 

Yes—provided the two theories or two methods are used deliberately to examine the same defined research question, and you compare what each contributes rather than merely listing them.

For your example—Hong Kong Gen Z residents’ experience of residential quality in co-living apartments—these are two distinct forms of triangulation:

Your design choice	Appropriate label	What it does
Two academic theories applied to the same evidence	Theoretical triangulation	Interprets the phenomenon through more than one conceptual lens
Two primary research methods used for the same question	Methodological triangulation	Builds evidence using more than one method and compares/integrates the findings

Triangulation is not a guarantee that both strands will produce identical results. The value is in identifying whether results converge, provide complementary insights, or diverge—and explaining why.pmc.ncbi.nlm.nih+2

Case 1: Two theories

Using two theories can be theoretical triangulation when each theory meaningfully frames or interprets residential-quality experience, rather than being decorative background literature. Theories should be compatible enough to be used together, but sufficiently distinct to add a different analytical angle.pmc.ncbi.nlm.nih+1

For example:

• Residential satisfaction / housing quality theory: evaluates perceived adequacy of space, facilities, privacy, safety, management and value for money.
• Place attachment theory: evaluates whether residents develop belonging, identification, emotional connection and a sense of “home” despite flexible leases and high resident turnover.

Three practical steps

1.    Assign a clear role to each theory.
State the same overarching question, such as: “How do Hong Kong Gen Z residents experience residential quality in co-living apartments?” Then define what each theory will examine. The first lens may assess functional and evaluative housing quality; the second may explain emotional and social experience of home.

2.    Develop one integrated analytical framework.
Turn both theories into interview topics, survey dimensions, or coding categories. For example, include privacy, crowding, shared amenities and management under residential quality; include belonging, neighbour interaction, stability and identification with the residence under place attachment. Avoid asking essentially identical questions under two theory labels.

3.    Analyse through each lens, then compare interpretations.
First report the findings according to Theory A, then Theory B. Finally, integrate them:

o   Convergence: Private rooms and good management improve both satisfaction and belonging.

o   Complementarity: Residents may rate facilities highly but still lack attachment because turnover prevents stable social relationships.

o   Divergence: Some residents may be satisfied precisely because co-living feels temporary and does not require emotional attachment.

This final comparison is the triangulation step—not simply using two theories in the literature review.bmj+1

Case 2: Two primary methods

Using, for instance, a survey plus semi-structured interviews is between-method methodological triangulation. Surveys can indicate the distribution and association of experiences across a broader group, while interviews can explore meaning, mechanisms and contradictions in depth. Methodological triangulation may combine qualitative and quantitative methods, but it can also use two different qualitative methods.pmc.ncbi.nlm.nih+1

A feasible part-time dissertation combination could be:

• An online survey of Hong Kong Gen Z co-living residents.
• Semi-structured interviews with a smaller purposive subsample of residents.

Three practical steps

1.    Specify shared constructs and the integration purpose.
Use the same core concept—residential quality—but decide what each method contributes. For example, the survey measures residents’ ratings of privacy, affordability, facilities, security, noise, social interaction and overall satisfaction. Interviews explore why these features matter and how residents negotiate shared living. This is often a practical pragmatist mixed-methods rationale.

2.    Collect and analyse each dataset rigorously on its own.
Analyse survey data using descriptive statistics and, if suitable for your sample, comparisons or associations. Analyse interviews with thematic analysis. Do not merge raw survey responses and interview quotations prematurely: each method needs a transparent sampling, data-collection and analysis procedure.

3.    Integrate results in a comparison matrix.
Place each key finding from the survey beside the related interview theme, then classify the relationship as convergence, complementarity or divergence. For example:

Residential-quality issue	Survey result	Interview result	Integrated interpretation
Privacy	Many respondents rate privacy poorly	Residents describe noise, thin walls and lack of control over common areas	Convergence: privacy is a central residential-quality problem
Social interaction	Average rating is neutral	Some value networking; others avoid common areas	Complementarity: “neutral” conceals sharply different experiences
Affordability	Most see rents as relatively acceptable	Residents say affordability is accepted only because the tenancy is short and location is convenient	Complementarity: affordability is conditional, not necessarily perceived as good value

A “joint display” or convergence matrix makes the integration visible to examiners and prevents a weak design in which a survey and interviews are reported as two unrelated mini-studies.bmj

Important distinction

Two theories plus two methods means you may use both theoretical and methodological triangulation in one dissertation. However, do not claim triangulation merely because you have more than one element. You need to show:

• One coherent research topic and aligned research questions.
• A justified reason each theory or method offers a distinct perspective.
• An explicit comparison and integrated interpretation of findings.
• Honest reporting of inconsistency rather than forcing agreement.

For a manageable part-time Housing Studies project, a strong formulation would be: “This study adopts theoretical triangulation by interpreting Gen Z co-living experiences through residential satisfaction and place attachment perspectives, and methodological triangulation by integrating a resident survey with semi-structured interviews.”

Lecture note on secondary data analysis: for Housing Studies students

Lecture note on secondary data analysis: for Housing Studies students

 

Highlight 5 main ideas of the secondary research method of secondary data analysis in the context of Housing Studies dissertation projects.

Secondary data analysis means answering a new research question by re-analysing data that another organisation or researcher originally collected for a different purpose. For a Housing Studies dissertation, it is especially useful when fieldwork access, time, or budget is limited.

Five main ideas

1.    Use analysable data, not only published statistics
Look for datasets with respondent-, household-, property-, or neighbourhood-level records (“microdata”), rather than only summary tables in annual reports. This allows you to test relationships—for example, whether overcrowding varies by household income, tenure type, or district.

2.    Match your research question to measurable variables
Break broad housing concepts into observable variables. For instance, “housing affordability” could be represented by rent-to-income ratio, monthly mortgage payment, household income, or housing expenditure burden. The video stresses that variables need to be available within the dataset and sufficiently close to the concept in the research question.

3.    Check the codebook before committing to a dataset
A codebook or data dictionary explains each variable, question wording, response categories, numeric codes, missing values, sample coverage, and collection method. Without it, a dataset may be impossible to interpret correctly; it is essential for judging whether “public housing,” “crowding,” “household,” or “income” has been defined in a way suitable for your dissertation.

4.    Ensure variables can be linked in the same dataset
To investigate an association, the relevant variables generally must appear for the same units of analysis. For example, a dissertation question such as “Is housing dissatisfaction associated with overcrowding among public-rental households?” requires records that contain tenure, crowding measures, and satisfaction responses for each relevant household—not three separate published tables.youtube

5.    Refine the question transparently around available data
Secondary-data projects often require a compromise between the ideal question and what existing data actually measure. You may begin with “How does housing quality affect wellbeing?” but revise it to “How is self-reported housing dissatisfaction associated with self-reported wellbeing among renters?” if those are the available variables. Clearly explain this operationalisation, its limitations, and why the measures are defensible in the methodology chapter.

Housing dissertation application

A practical workflow is:

1.    Define the population and unit of analysis: individual, household, dwelling, estate, district, or transaction.

2.    List the concepts in your question and the variables needed for each.

3.    Locate relevant public, institutional, survey, census, transaction, or administrative datasets.

4.    Read the dataset documentation and assess its date, geography, sampling, missing data, and access restrictions.

5.    Align the final research question, hypotheses, method, and limitations with what the dataset can validly support.

For a Hong Kong-focused project, this approach could support topics such as affordability, public-housing mobility, housing satisfaction, overcrowding, spatial inequality, ageing households, or the relationship between tenure and wellbeing—provided the selected dataset includes properly documented variables for those constructs.