Chapter 1: Introduction to Knowledge Production

Introduction

  • Lecture refers to K 1000 class on January 26

  • Lecture is recorded instead of in-class due to campus operation suspension from snow

  • A piece by composer Barbara Strozzi played to illustrate a point

Unit Overview: Whose Knowledge Counts

  • Focuses on:

    • How knowledge is produced

    • What knowledge is deemed important

    • Who gets to produce knowledge

  • Announcements:

    • Mind Map 3 due next week

    • Key terms and predrawn mind map will be provided

    • Instructions and key terms will be in a document sent next week

    • Tutorial leaders will email regarding participation and updates on other courses

Connecting Previous Units

  • Encouragement to link unit’s themes with previous units:

    • Critical Thinking

    • Sociological Imagination

    • Settler Colonialism

    • Race and Racialization

    • Identities

    • The unit on Other Bodies

  • Key concept:

    • The question of whose knowledge counts implies that some knowledge may be marginalized

Knowledge Production Methods

Qualitative Research Methods

  • Definition: A way of studying things in their real-life environment to understand the "how" and "why" behind them

  • Focus on understanding:

    • How and why events happen

  • Types of questions:

    • Explore people’s experiences and interpretations

  • Aim for depth and richness in data collection

  • Limitations:

    • Generally has a smaller sample size, not intended to generalize to a larger population

Quantitative Research Methods

  • Definition: Research method focused on numerical data and statistical analysis

  • Emphasis:

    • Understanding the reality of what is happening (answers “what is happening?”)

  • Methods of data collection:

    • Polls, surveys, questionnaires

  • Advantages:

    • Larger sample sizes permit generalizations about wider populations

Mixed Methods

  • Combination of qualitative and quantitative methods in research

  • Purpose:

    • To gain a fuller understanding, bridging data sets through qualitative insights

Objectivity vs Subjectivity in Knowledge

Objective Knowledge

  • Defined by the concept of distance between researcher and object of study

  • Belief: Objectivity is superior and is more trustworthy

  • Critique: Assumes emotional detachment, main source of perceived reliability

Subjective Knowledge

  • Defined by personal values, assumptions, and emotions within research contexts

  • Critique: Seen as biased and less reliable

  • Bias Definition: Unintended errors in research due to researchers’ expectations

Mind-Body Dualism

  • Historical view that rational thought (mind) is superior to emotion (body)

  • Subjectivity viewed as detrimental to objective research

Social Constructivism Paradigm

  • Assumes that complete objectivity in research is not achievable

  • Highlights the importance of personal factors in shaping knowledge production

  • Encourages examination of personal assumptions and values in research

Example: Barbara Strozzi

  • Strozzi: First woman to publish her music under her own name

  • Highlights the challenges women faced in knowledge production

Women in Science

Film: Picture a Scientist

  • Discusses systemic discrimination women face in STEM fields

  • Highlights issues like underrepresentation and biases women scientists endure

  • Importance of addressing these biases to advocate for equitable knowledge production

Politics of Research and Worthwhile Subjects

Political Context in Research

  • Research is influenced by historical and political contexts

  • Discussion on the anatomy focus (e.g., penis vs. clitoris)

  • Historical differences in research focus reflect broader gender biases

The Clitoris Study

  • Doctor O'Connell's work in the 1990s on the clitoris

  • Findings: Vast underrepresentation of female anatomy research

  • Only 11 anatomical dissection studies published from 1947 to 2020

Ethical Considerations in Research Design

Top-Down Approaches

  • History of research marginalized groups using a top-down approach

  • Othering: The process of making an individual or group appear foreign or inferior

  • The historical context of research practices involving Indigenous peoples and people of color

Collaborative Research Approaches

  • Emphasis on community-based research models

  • Discusses the principles of meaningfulness, community involvement, and knowledge mobilization

  • Importance of adhering to ethical guidelines when working with Indigenous communities, such as following Indigenous research protocols

Conclusion

  • Importance of examining who produces knowledge and the biases inherent within research practices

  • Discussion of a new paradigm that includes equitable and just knowledge production strategies to counteract historical injustices and biases

  • Call for community involvement and active participation in shaping research agendas

Final Remarks

  • Encouragement for students to reach out for assistance or questions in their academic journey.

Mixed methods refer to the integration of both qualitative and quantitative research approaches in order to provide a more comprehensive understanding of research questions. Examples of mixed methods include:

  1. Concurrent Triangulation Design

    • Both qualitative and quantitative data are collected simultaneously.
    • Example: A survey (quantitative) combined with focus groups (qualitative) to assess student satisfaction.

  2. Sequential Explanatory Design

    • Quantitative data is collected first, followed by qualitative data to explain the quantitative findings.
    • Example: Conducting a large-scale survey (quantitative) to identify trends, followed by interviews (qualitative) to dive deeper into those trends.

  3. Sequential Exploratory Design

    • Qualitative data is collected first to explore a phenomenon, then quantitative data is collected to test or validate the initial findings.
    • Example: Conducting interviews (qualitative) to explore experiences of a new program, which leads to developing a survey (quantitative) for broader testing.

  4. Embedded Design

    • Qualitative and quantitative methods are embedded within a larger framework of one approach.
    • Example: A randomized controlled trial (quantitative) that also includes qualitative interviews with participants to gather insights about their experiences during the trial.