Assignment task:
In depth respond to the below post. Include two APA sources and one bible verse. Make 2 questions for each response to help them develop their research more.
King et al. (1994) provides several important recommendations for dealing with bias in research. Being explicit about assumptions and theories allows others to critique and test them, reducing potential blind spots. Consciously avoiding or correcting for selection bias in how observations are included ensures the sample is representative and avoids systemic skew (p. 115). Collecting more observations through larger sample sizes increases statistical power and helps reduce random noise (King et al., 1994, p.182). When possible, randomization through experimental or natural experiment approaches should be used to avoid confounding and selection issues and isolate causal effects (King et al., 1994, p.156). Seeking out diverse data sources from multiple perspectives helps guard against biases inherent in any single data collection method or source.
In their seminal paper, Angrist and Pischke (2010) highlight the "credibility revolution" that has reshaped empirical economics over recent decades. This revolution is driven by an increased focus on implementing research designs that enhance causal inference and internal validity. They emphasize the greater use of natural experiments and quasi-experimental designs like regression discontinuity over correlational studies alone (Angrist & Pischke, 2010, p.6). They argue for prioritizing robust identification strategies aimed at isolating causal effects rather than merely controlling for observable confounding variables statistically (Angrist & Pischke, 2010, p. 7). Their work advocates taking direction from the theory of potential outcomes and counterfactual models from Statistics (Angrist & Pischke, 2010, p.11). Finally, they encourage researchers to be upfront about which questions can and cannot be credibly answered given limitations in available data and designs.
These principles from Angrist and Pischke (2010) are highly relevant to public policy research, which often evaluates the causal impacts of interventions, programs, and policy changes. Using stronger empirical designs and explicitly discussing identification strategies enhances reliability and validity (Angrist & Pischke, 2010, p.17). Potential outcomes framing focuses on treatments versus controls and maps cleanly to program evaluation contexts. As Angrist and Pischke note, leveraging natural experiments created by policy rules and eligibility criteria provides powerful opportunities for credible inference in policy analysis (Angrist & Pischke, 2010, p.18). However, researchers must still be candid about the remaining limitations.
If statesmen and policy leaders abandon ethical principles and norms of integrity, the consequences can be dire. Ethics serve as essential guardrails for government action and underpin public trust in institutions (Weimer & Vining, 2017, p.48). Without ethics, leaders may prioritize raw power over democratic accountability, human rights, and anti-corruption efforts (p. 53). The atrocities of WWII, Soviet oppression, and the Rwandan genocide all stem from moral failings. Even in modern democracies, unethical conduct like Watergate severely undermines faith in government (p. 55).
Abandoning ethics risks policies being made based on politically practical lies, distorted evidence, and conflicts of interest rather than the pursuit of the public good (Weimer & Vining, 2017, p. 49). Ethical principles of honesty, reason, and impartiality are vital for sound policy analysis and decision-making. Conversely, without morality, it becomes far more likely policies will serve narrow special interests over the broader rights and welfare of citizens (p. 56). Thus, ethical leadership is essential for just, evidence-based policymaking.
References