Readings Flashcards
statement of relations among concepts within a set of boundary assumptions and constraints. It is no more than a linguistic
device used to organize a complex empirical
world.
Theory
f preventing the observer from being dazzled by the full blown complexity of natural or concrete events
Function of theory
Purpose of theoretical statements
- to organize (parsimoniously) (karig, simpel)
- to communicate (clearly)
Features or quality of individual things, acts or events
Description (different than theories)
Three types of description
- categorisation of raw data
- categorisation of typologies
- Categorisation of metaphors
Empirically categorising things (type of description)
categorisation of raw data
Mental construct formed by the synthesis of many individual phenomena
which are arranged according to certain points of view (more abstract than categ. of raw data) (type of description
categorisation of typologies
Statement that says that two phenomena are isomorphic (have characteristics
in common)
(type of description
categorisation of metaphors
Statement of relationships between units observed or approximated in the empirical world, answers the questions how, when, why, system of constructs and variables in which the constructs are related to each other by propositions and the variables are related to each other by hypotheses, bounded by theorist’s assumptions
Theory
Constructs which by their nature can’t be observed directly
Approximated units
Variables which are empirically operationalised by measurement
observed units
Based on assumptions about value time and space (implicit values of theorist, explicit restrictions [limit theory to specific units of analysis])
boundaries of theories
Whether a theory is constructed such that empirical refutation (act of disproving or challenging) is possible, theory can’t be proven but only disproven.
falsifiability
Two primary criteria upon which any theory may be evaluated
falsifiability and utility
Usefulness of theoretical system, bridge that connects theory and research, theory is useful if it can explain and predict, often only good for prediction but does not provide explanation
Utility
Theory is useful when … : core elements of utility
- explanation
- prediction
Types of falsifiability
- falsifiability of variables
- falsifiability of constructs
- Falsifiability of relationship
Types of utility
- utility of variables and constructs
- utility of relationships
Falsifiability of variables
Measurement issues, variables must be coherent (validity, noncontinuousness,
reliability)
falsifiability of constructs
Construct validity. one can empirically differentiate the construct from other constructs that may be similar, and that one can point out what is unrelated to the
construct, construct validity can only be rejected and not confirmed.
criteria of Falsifiability of Relationships
Logical and Empirical Adequacy
Implicit or explicit logic embedded in the hypotheses and propositions which
ensures that hypotheses and propositions are capable of being disconfirmed. must be nontautological (meaningful, substantive information_ and nature of relationship between antecedent and consequent must be specified
Logical adequacy
Propositions and hypotheses can be operationalised in a way that allows the
theory to be disconfirmed
Empirical adequacy
THe utility of variables and contstructs
Scope.
Variables included must tap the domain of the construct, constructs
must tap the domain of the phenomenon in question
Utility of relationships:
Explanatory Potential and
Predictive Adequacy
Do you have predictive theory for theory to be acceptable? degree to which
hypotheses and propositions approximate reality
Predictive adequacy
Two types of prediction
- probabilistic
- theory based
Based on universal law of probability
probabilistic predicton
Grounded in propositions and deduced hypotheses, made in specific period of
time and number of cases
THeory based prediction
Ability of a new theory to bridge gap between two or more different theories, explaining something between domains of previous theories, new knowledge is created
connective theory
Causes preexisting theory to be reevaluated in a new light
Transformational theory
Which data is not good for addressing questions about causality or change because of time factor?
cross sectional data
Causal inference needs …. or … data
longitudinal panel or experimental
Practical problems confronting researchers as they design studies
- there are no hard and fast rules to apply
- external factors sometimes constrain researchers’ ability to carry out optimal designs
three broad design problems that were common sources of rejection
- Mismatch between research question and research design (cross sectional data and inappropriate samples and procedures)
- measurement and operational issues (construct validity)
- inappropriate or incomplete model specification.
Mismatch between RQ and research design because of:
Cross-sectional data
inappropriate samples and procedures
measurement and operational issues (construct validity) because of:
- Inappropriate adaptation of existing measures
- Inappropriate application of existing mea
sures - Common method variance
presents a serious threat to interpretation of observed correlations, because such
correlations may be the result of systematic error variance due to measurement methods
Common method variance
Model specification through
- Proper inclusion of control variables
- Operationalizing mediators
Framing of research project (MRC)
The audience and prior research
RQ
THe nucleus of the MRC
the puzzle
The Theoretical framework (MRC)
Theoretical constructs and relationships
Empirical methods (MRC)
Research setting
Research design and analysis
Conclusions (MRC)
Empirical findings
Contributions
Boundary conditions and limitations
THree fundamental characteristics of qualitiative data that offer potential advantages over quantitative data
- open-ended (: No need to predetermine precise constructs and measures to collect qualitative data)
- concrete and vivid (Activate cognitive processes that foster development and communication of ideas)
- rich and nuanced ( Capture details and mechanisms that are overlooked in quantitative data)
Reasons to use qualitative data
- To build new theory when prior theory is absent, underdeveloped, or flawed
- To capture individuals’ lived experiences and interpretations
- To understand complex process issues
- To illustrate an abstract idea
- To examine narratives, discourse, or other linguistic phenomena
challenges of qualitative research in review prcoess/publication process
- writing the ‘front-end’ (establishes that the topic is new)
- Describing analysis
- Addressing biases
Create interest in article, show why it is relevant, identify primary literature, set out
assumptions and boundary conditions
Common ground
Present problem/puzzle in academic discussion, show missing element of current research
complication
Explain why gap in research (complication) matters
concern
How you address and resolve central complication, argue that it is relevant
and effective.
Course of action
This entails explaining how your work will shape or change the conversation
contribution
Pitfalls of grounding the hypotheses
- Lack of specifity
- fragmented theorizing
- stating the obvious
Pitfalls of theory section
- argument by citiation
- ignoring prior related conversation (not enough citations)
THeory section should ground hyptoheses by:
- Positioning hypotheses in relation to related research
- Develop a clear, logical argument why core variables/processes are related
- Create a sense of coherence in the relationships among the variables and processes
In theory section, develop a clear, logical argument why core variables/processes are related when :
- substantiating hypotheses
- multiple theories are used
how these variables fit together
in a way that creates a strong theoretical contribution
coherence
