😶‍🌫️
Psych
  • Preface
  • [4/9/2025] A One-Stop Calculator and Guide for 95 Effect-Size Variants
  • [4/9/2025] the people make the place
  • [4/9/2025] Personality predicts things
  • [3/31/2025] Response surface analysis with multilevel data
  • [3/11/2025] A Complete Guide to Natural Language Processing
  • [3/4/2025] Personality - Self and Identity
  • [3/1/2025] Updating Vocational Interests Information
  • [2/25/2025] Abilities & Skills
  • [2/22/2025] APA table format
  • [2/19/2025] LLM that replace human participants can harmfully misportray and flatt
  • [2/18/2025] Research Methods Knowledge Base
  • [2/17/2025] Personality - Motives/Interests
  • [2/11/2025] Trait structure
  • [2/10/2025] Higher-order construct
  • [2/4/2025] RL for CAT
  • [2/4/2025] DoWhy | An end-to-end library for causal inference
  • [2/4/2025] DAGitty — draw and analyze causal diagrams
  • [2/2/2025] Personality States
  • [2/2/2025] Psychometric Properties of Automated Video Interview Competency Assessments
  • [2/2/2025] How to diagnose abhorrent science
  • [1/28/2025] LLM and personality/interest items
  • [1/28/2025] Personality - Dispositions
  • [1/28/2025] Causal inference in statistics
  • [1/27/2025] Personality differences between birth order categories and across sibship sizes
  • [1/27/2025] nomological network meta-analysis.
  • [1/25/2025] Classic Papers on Scale Development/Validation
  • [1/17/2025] Personality Reading
  • [1/15/2025] Artificial Intelligence: Redefining the Future of Psychology
  • [1/13/2025] R for Psychometics
  • [12/24/2024] Comparison of interest congruence indices
  • [12/24/2024] Most recent article on interest fit measures
  • [12/24/2024] Grammatical Redundancy in Scales: Using the “ConGRe” Process to Create Better Measures
  • [12/24/2024] Confirmatory Factor Analysis with Word Embeddings
  • [12/24/2024] Can ChatGPT Develop a Psychometrically Sound Situational Judgment Test?
  • [12/24/2024] Using NLP to replace human content coders
  • [11/21/2024] AI Incident Database
  • [11/20/2024] Large Language Model-Enhanced Reinforcement Learning
  • [11/05/2024] Self-directed search
  • [11/04/2024] Interview coding and scoring
  • [11/04/2024] What if there were no personality factors?
  • [11/04/2024] BanditCAT and AutoIRT
  • [10/29/2024] LLM for Literature/Survey
  • [10/27/2024] Holland's Theory of Vocational Choice and Adjustment
  • [10/27/2024] Item Response Warehouse
  • [10/26/2024] EstCRM - the Samejima's Continuous IRT Model
  • [10/23/2024] Idiographic Personality Gaussian Process for Psychological Assessment
  • [10/23/2024] The experience sampling method (ESM)
  • [10/21/2024] Ecological Momentary Assessment (EMA)
  • [10/20/2024] Meta-Analytic Structural Equation Modeling
  • [10/20/2024] Structure of vocational interests
  • [10/17/2024] LLMs for psychological assessment
  • [10/16/2024] Can Deep Neural Networks Inform Theory?
  • [10/16/2024] Cognition & Decision Modeling Laboratory
  • [10/14/2024] Time-Invariant Confounders in Cross-Lagged Panel Models
  • [10/13/2024] Polynomial regression
  • [10/13/2024] Bayesian Mixture Modeling
  • [10/10/2024] Response surface analysis (RSA)
  • [10/10/2024] Text-Based Personality Assessment with LLM
  • [10/09/2024] Circular unidimensional scaling: A new look at group differences in interest structure.
  • [10/07/2024] Video Interview
  • [10/07/2024] Relationship between Measurement and ML
  • [10/07/2024] Conscientiousness × Interest Compensation (CONIC) model
  • [10/03/2024] Response modeling methodology
  • [10/02/2024] Conceptual Versus Empirical Distinctions Among Constructs
  • [10/02/2024] Construct Proliferation
  • [09/23/2024] Psychological Measurement Paradigm through Interactive Fiction Games
  • [09/20/2024] A Computational Method to Reveal Psychological Constructs From Text Data
  • [09/18/2024] H is for Human and How (Not) To Evaluate Qualitative Research in HCI
  • [09/17/2024] Automated Speech Recognition Bias in Personnel Selection
  • [09/16/2024] Congruency Effect
  • [09/11/2024] privacy, security, and trust perceptions
  • [09/10/2024] Measurement, Scale, Survey, Questionnaire
  • [09/09/2024] Reporting Systematic Reviews
  • [09/09/2024] Evolutionary Neuroscience
  • [09/09/2024] On Personality Measures and Their Data
  • [09/09/2024] Two Dimensions of Professor-Student Rapport Differentially Predict Student Success
  • [09/05/2024] The SAPA Personality Inventory
  • [09/05/2024] Moderated mediation
  • [09/03/2024] BiGGen Bench
  • [09/02/2024] LMSYS Chatbot Arena
  • [09/02/2024] Introduction to Measurement Theory Chapters 1, 2 (2.1-2.8) and 3.
  • [09/01/2024] HCI measurememt
  • [08/30/2024] Randomization Test
  • [08/30/2024] Interview Quantative Statistical
  • [08/29/2024] Cascading Model
  • [08/29/2024] Introduction: The White House (IS_202)
  • [08/29/2024] Circular unidimensional scaling
  • [08/28/2024] Sex and Gender Differences (Neur_542_Week2)
  • [08/26/2024] Workplace Assessment and Social Perceptions (WASP) Lab
  • [08/26/2024] Computational Organizational Research Lab
  • [08/26/2024] Reading List (Recommended by Bo)
  • [08/20/2024] Illinois NeuroBehavioral Assessment Laboratory (INBAL)
  • [08/14/2024] Quantitative text analysis
  • [08/14/2024] Measuring complex psychological and sociological constructs in large-scale text
  • [08/14/2024] LLM for Social Science Research
  • [08/14/2024] GPT for multilingual psychological text analysis
  • [08/12/2024] Questionable Measurement Practices and How to Avoid Them
  • [08/12/2024] NLP for Interest (from Dan Putka)
  • [08/12/2024] ONet Interest Profiler (Long and Short Scale)
  • [08/12/2024] ONet Interests Data
  • [08/12/2024] The O*NET-SOC Taxonomy
  • [08/12/2024] ML Ratings for O*Net
  • [08/09/2024] Limited ability of LLMs to simulate human psychological behaviours
  • [08/08/2024] A large-scale, gamified online assessment
  • [08/08/2024] Text-Based Traitand Cue Judgments
  • [08/07/2024] Chuan-Peng Lab
  • [08/07/2024] Modern psychometrics: The science of psychological assessment
  • [08/07/2024] Interactive Survey
  • [08/06/2024] Experimental History
  • [08/06/2024] O*NET Research reports
  • [07/30/2024] Creating a psychological assessment tool based on interactive storytelling
  • [07/24/2024] My Life with a Theory
  • [07/24/2024] NLP for Interest Job Ratings
  • [07/17/2024] Making vocational choices
  • [07/17/2024] Taxonomy of Psychological Situation
  • [07/12/2024] PathChat 2
  • [07/11/2024] Using games to understand the mind
  • [07/10/2024] Gamified Assessments
  • [07/09/2024] Poldracklab Software and Data
  • [07/09/2024] Consensus-based Recommendations for Machine-learning-based Science
  • [07/08/2024] Using AI to assess personal qualities
  • [07/08/2024] AI Psychometrics And Psychometrics Benchmark
  • [07/02/2024] Prompt Engineering Guide
  • [06/28/2024] Observational Methods and Qualitative Data Analysis 5-6
  • [06/28/2024] Observational Methods and Qualitative Data Analysis 3-4
  • [06/28/2024] Interviewing Methods 5-6
  • [06/28/2024] Interviewing Methods 3-4
  • [06/28/2024] What is Qualitative Research 3
  • [06/27/2024] APA Style
  • [06/27/2024] Statistics in Psychological Research 6
  • [06/27/2024] Statistics in Psychological Research 5
  • [06/23/2024] Bayesian Belief Network
  • [06/18/2024] Fair Comparisons in Heterogenous Systems Evaluation
  • [06/18/2024] What should we evaluate when we use technology in education?
  • [06/16/2024] Circumplex Model
  • [06/12/2024] Ways of Knowing in HCI
  • [06/09/2024] Statistics in Psychological Research 1-4
  • [06/08/2024] Mathematics for Machine Learning
  • [06/08/2024] Vocational Interests SETPOINT Dimensions
  • [06/07/2024] How's My PI Study
  • [06/06/2024] Best Practices in Supervised Machine Learning
  • [06/06/2024] SIOP
  • [06/06/2024] Measurement, Design, and Analysis: An Integrated Approach (Chu Recommended)
  • [06/06/2024] Classical Test Theory
  • [06/06/2024] Introduction to Measurement Theory (Bo Recommended)
  • [06/03/2024] EDSL: AI-Powered Research
  • [06/03/2024] Perceived Empathy of Technology Scale (PETS)
  • [06/02/2024] HCI area - Quantitative and Qualitative Modeling and Evaluation
  • [05/26/2024] Psychometrics with R
  • [05/26/2024] Programming Grammer Design
  • [05/25/2024] Psychometric Network Analysis
  • [05/23/2024] Item Response Theory
  • [05/22/2024] Nature Human Behaviour (Jan - 20 May, 2024)
  • [05/22/2024] Nature Human Behaviour - Navigating the AI Frontier
  • [05/22/2024] Computer Adaptive Testing
  • [05/22/2024] Personality Scale (Jim Shard)
  • [05/22/2024] Reliability
  • [05/19/2024] Chatbot (Jim Shared)
  • [05/17/2024] GOMS and Keystroke-Level Model
  • [05/17/2024] The Psychology of Human-Computer Interaction
  • [05/14/2024] Computational Narrative (Mark's Group)
  • [05/14/2024] Validity Coding
  • [05/14/2024] LLM as A Evaluator
  • [05/14/2024] Social Skill Training via LLMs (Diyi's Group)
  • [05/14/2024] AI Persona
  • [05/09/2024] Psychological Methods Journal Sample Articles
  • [05/08/2024] Meta-Analysis
  • [05/07/2024] Mturk
  • [05/06/2024] O*NET Reports and Documents
  • [05/04/2024] NLP and Chatbot on Personality Assessment (Tianjun)
  • [05/02/2024] Reads on Construct Validation
  • [04/25/2024] Reads on Validity
  • [04/18/2024] AI for Assessment
  • [04/17/2024] Interest Assessment
  • [04/16/2024] Personality Long Reading List (Jim)
    • Personality Psychology Overview
      • Why Study Personality Assessment
    • Dimensions and Types
    • Reliability
    • Traits: Two Views
    • Validity--Classical Articles and Reflections
    • Validity-Recent Proposals
    • Multimethod Perspective and Social Desirability
    • Paradigm of Personality Assessment: Multivariate
    • Heritability of personality traits
    • Classical Test-Construction
    • IRT
    • Social desirability in scale construction
    • Traits and culture
    • Paradigms of personality assessment: Empirical
    • Comparison of personality test construction strategies
    • Clinical versus Actuarial (AI) Judgement and Diagnostics
    • Decisions: Importance of base rates
    • Paradigms of Personality Assessment: Psychodynamic
    • Paradigms of Assessment: Interpersonal
    • Paradigms of Personality Assessment: Personological
    • Retrospective reports
    • Research Paradigms
    • Personality Continuity and Change
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[08/29/2024] Introduction: The White House (IS_202)

Previous[08/29/2024] Cascading ModelNext[08/29/2024] Circular unidimensional scaling

Last updated 9 months ago

This chapter provides a personal account of the author's childhood growing up in the "White House" in Los Angeles, and how this experience shaped their perspective on justice and abolition. It then transitions to the tragic story of Breonna Taylor, a Black woman killed by police in her own home during the COVID-19 pandemic. The document explores themes of community, family, and the need for transformative justice to address systemic racism and violence.

Key Points

  • The author grew up in a close-knit community in the "White House" in Los Angeles, where their grandmother modeled an abolitionist approach of care and connection rather than punishment.

  • The author reflects on the constant threat of violence and conflict they felt growing up, and how their grandmother's approach taught them a different way of responding.

  • The story of Breonna Taylor's killing by police in her own home during the COVID-19 pandemic is used to illustrate the urgent need for transformative justice to address systemic racism and violence.

  • It explores themes of community, family, and the power of alternative approaches to justice and safety that center care, healing, and collective well-being.

Questions for Discussions

  1. How did the author's upbringing in diverse communities shape their perspective on justice and abolition?

  2. What lessons did the author learn from their grandmother's abolitionist approach of care and connection rather than punishment?

  3. How does the story of Breonna Taylor's killing illustrate the need for transformative justice to address systemic racism and violence?

  4. What parallels can be drawn between the ongoing efforts to rewrite Chile's constitution and the need to reimagine our own political and economic systems?

  5. How can individuals challenge "the machinery of our everyday lives" and disrupt the status quo through small, everyday actions?

  6. What are the risks of becoming an "Antiracism Police" and how can we avoid reproducing the same logics of policing and harassment?

  7. How can we balance the need for structural, macro-level change with the importance of individual decisions and actions in driving social transformation?

  8. What does it mean to "reclaim power over how our thoughts, habits, and actions shape—as much as they are shaped by—the larger environment"?

Some Additional Questions

  1. How does the author's personal experience with the cracked window and fear of violence as a child connect to the story of Breonna Taylor's killing?

  2. What insights does the concept of "weathering" provide about the systemic factors that contributed to the author's father's premature death?

  3. How does the author's diverse upbringing and exposure to different "worlds" shape their perspective on the need for transformative change?

  4. What does the author mean by the "dirty secret of antisocial policies" and how does it challenge the notion of individual responsibility?

  5. How does the author's shift in thinking from a focus on structural change to the importance of individual actions and decisions reflect a broader tension in approaches to social justice?

  6. What examples does the author provide of how "small things" and "seemingly minor actions, decisions, and habits" can have exponential effects in driving positive change?

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BENJAMIN-INTRODUCTION-2022.pdf
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