Compare the characters that differentiate phyla classified as Lophotrochozoa and phyla classified as Ecdysozoa. What features would help you distinguish between these two? Making a chart would probably be helpful! Describe the characteristics of the major Lophotrochozoan phyla (Platyhelminthes, Annelida, Mollusca).

Discuss the importance of group differences in IQ for understanding intelligence.

Considering the article Can Research on the Genetics of Intelligence Be ‘Socially Neutral’? and the textbook chapters on intelligence, compare and discuss at least two group differences in IQ. Why are these differences important for understanding intelligence?

After you have posted your initial response, respond to two of your peers. Discuss some of the factors that were identified to influence intelligence testing (e.g., ethics or cultural differences) and provide a rationale as to why some of these factors may or may not be more influential than others.

 

Text:

Roberts, D. (2015). Can Research on the Genetics of Intelligence Be “Socially Neutral”? Hastings Center Report, 45, S50-S53. https://doi-org.ezproxy.snhu.edu/10.1002/hast.499

During the first semester, course readings and lectures introduced, defined, and discussed the following concepts: mental models, business-as-usual, uncertainty, Anthropocene, shifting baseline syndrome, Default cognitive patterns, Capitalocene, “Seven Cheap Things,” environmental migration, and “climate refugee.” Develop a short essay answer that defines one of these concepts and discusses its relevance to the work of representing climate change. The answer must develop a coherent essay structure, which includes an argument and supporting evidence from at least two references to additional course materials.

 

Patel, R. and Moore, J. (2017). “Introduction” (p.1-8), in A History of the World in Seven Cheap Things: A Guide to Capitalism, Nature, and the Future of the Planet. Oakland, CA: the University of California Press.
Weart, S. (2012). “The Development of the Concept of Dangerous Anthropogenic Climate Change” (p.62-73), In Dryzek, J., et al. (eds). Oxford Handbook of Climate Change and Society. Oxford, UK: Oxford University Press.

 

Due to the binary nature of the dependent variables, multilevel logistic regression models were specified using STATA 13. The analyses began with the estimation of a null model (i.e., unconditional model) with no school-level variables in order to ascertain an estimation of the intraclass correlation coefficient (Snijders & Bosker, 2012). The models fit with demographic variables as the Level-1 indicators (e.g., individual-level factors). Random intercepts were found to be statistically significant, confirming the need to account for variation between the schools in the model. The Level-2 variables (school-level variables) were included in the model as part of the model-building process. All school-level variables were aggregated to the school level. Standardized coefficients were calculated for ease of interpretation across models (Tabachnick & Fidell, 2007). The current study represents a

secondary data analysis and statistical power was not calculated a priori. Research suggests a Level-2 sample greater than 50 to yield 80% power for logistic multilevel modeling (Ali et al., 2019; Moineddin et al., 2007). The current study had a smaller Level-2 sample than is recommended and may have resulted in underpowered models. However, the analyses produced results large enough to detect statistically significant effects.

Results

Among the students in the sample, 37.4% reported harassment victimization, 10.4% reported harassment perpetration, 9.5% reported sexual assault victimization, 1.8% reported sexual assault perpetration, 23.1% reported dating violence victimization, and 13.8% reported dating violence perpetration in the past year. The intraclass correlations (ICCs) were calculated via the creation of null models (i.e., uncondi- tional models). The null models excluded all independent variables to assess the variation of the dependent variables across the schools. The ICCs for each of the six outcomes were as follows: 1.8% for harassment victimization, 1.1% for harassment perpetration, 3.8% for sexual assault victimization, .9% for sexual assault perpetration, 6.3% for dating violence victimization, and 4.2% for dating violence perpetra- tion. These ICCs indicate the extent to which variation in the outcome is attributable to school-level rather than individual-level factors. Despite low percentages for the ICCS, they are above zero indicating that there is some difference in the variation of each outcome relative to school. Thus, Level-1 and Level-2 variables were included in the models. Table 2 presents the result of the multilevel models.

Hypothesis 1: Schools where staff express more positive school climates will have lower probabilities of school-level interper- sonal victimization and perpetration.

Consistent with Hypothesis 1, we found that staff reactive bystander intentions were significantly associated with a lower probability of harassment victimization (OR = .93, SE = .04, p < .05) and dating violence perpetration (OR = .87, SE = .05, p < .01). Also consistent with Hypothesis 1, staff readiness to address violence was associated with a lower probability of harassment victimization (OR = .95, SE = .01, p < .001), harassment perpetration (OR = .94, SE = .02, p < .01), sexual assault victimization (OR = .95, SE = .02, p < .05), sexual assault perpetration (OR = .91, SE = .04, p < .05), dating violence victimization (OR = .96, SE = .02, p < .05), and dating violence perpetration (OR = .94, SE = .02, p < .001). Inconsistent with hypothesis 1, we found that staff proactive bystander intentions were significantly associated with a higher probability of dating violence perpetration (OR = 1.01, SE = .04, p <.05). Staff bystander barriers and efficacy were not found to be significantly related to any forms of interpersonal violence.

Hypothesis 2: School and community composition will be related to higher probabilities of school-level interpersonal victimization and perpetration.

Consistent with Hypothesis 2, we found that student population size was significantly associated with a higher likelihood of sexual assault victimization (OR = 1.00, SE = .00, p < .05), dating violence victimization (OR = 1.00, SE = .00, p < .05), and dating violence perpetration (OR = 1.00, SE = .00, p < .050). Large town population was significantly associated with a higher likelihood of harassment victimization (OR = 1.00, SE = .00, p < .05), sexual assault victimization (OR = 1.00, SE = .00, p < .05), dating vio- lence victimization (OR = 1.00, SE = .00, p < .001), and dating violence perpetration, consistent with hypothesis two. A higher proportion of girls relative to boys at the school-level was related to a lower probability of dating violence perpetration (OR = .95, SE = .03, p < .05), consistent with Hypothesis 2. Finally, consistent with Hypothesis 2, school-level poverty was significantly associ- ated with a higher probability of dating violence victimization (OR = 1.02, SE = .01, p < .01) and dating violence perpetration (OR = 1.02, SE = .01, p < .01). No other composition variables were associated with interpersonal violence.

Hypothesis 3: Individual-level factors will be significantly associated with interpersonal victimization and perpetration.

At the individual-level, male students relative to female students were significantly associated with a lower likelihood of harassment victimization (OR = .33, SE = .08, p <.001)., sexual assault victimi- zation (OR = .28, SE = .15, p <.001), dating violence victimization (OR = .65, SE = .09, p <.001), and dating violence perpetration (OR = .58, SE = .11, p <.001) and a higher likelihood of harassment perpetration (OR = 1.77, SE = .12, p <.001). White non-Hispanic students relative to minority students were associated with a lower probability of harassment perpetration (OR = .69, SE = .17, p <.05). Sexual minority status was significantly associated with higher probabilities of harassment victimization (OR = 2.52, SE = .12, p <.001), harassment perpetration (OR = 2.70, SE = .15, p <.001), sexual assault victimization (OR = 2.08, SE = .16, p <.001), sexual assault perpetration (OR = 2.32, SE = .33, p <.01), dating violence victimization (OR = 1.55, SE = .12, p <.001), and dating violence perpetration (OR = 1.55, SE = .15, p <.01). Finally, older students relative to younger students had a higher probability of sexual assault victimization (OR = 1.29, SE = .05, p <.001), sexual assault perpetration (OR = 1.45, SE = .11, p <.05), dating violence victimization (OR = 1.20, SE = .04, p <.001), and dating violence perpetration (OR = 1.26, SE = .05, p <.001).

Consider historical factors: describe the ways deinstitutionalization has impacted patient rights, levels of care, and access to treatment of the disorders over time. The disorders are bipolar disorder, Asperger syndrome, and schizophrenia.