Implementing aspects of Blueprint 2000: Investigating readiness expectations in selected elementary schools in Broward County, Florida

The purpose of this research study was to investigate if the determination of school readiness as it was evaluated by Broward County kindergarten teachers on the Florida's Expectations of School Readiness checklist can be attributed to the effects of gender, chronological age on school entry, racial or ethnic background, attending public preschool, native language other than English, or socioeconomic status.^ This is a descriptive study in which the number of expectations passed or failed for each of the identifier categories was compared. The Chi-squared distribution was used to evaluate the null hypothesis that "chronological age at entry to school, gender, race or ethnicity, native language other than English, public preschool experience, and socioeconomic status have no effect on the determination of readiness for school". Results were confirmed using t-tests, ANOVA, and linear regression models. The cohort of 1555 Broward County students in the study were evaluated using the Florida's Expectations for School Readiness checklist and were determined not ready for school during the initial data collection year 1996-1997.^ The determination of school readiness was significantly dependent on the gender, and racial or ethnic background of the students in the cohort. The socioeconomic status and native language other than English designations were significant for students only in the areas of preacademic, academic and literacy development. Chronological age on entry to school or attendance in public preschool prior to entry in kindergarten for the cohort was not significant in the determination of readiness for school.^ Given the fact that this study followed only students that were determined not ready for school, it is recommended that a second cohort of both "ready" and "not ready" students be studied. ^

An autoregressive conditional filtering process to remove intraday seasonal volatility and its application to testing the noisy rational expectations model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

The boundaries of acceptance: Do expectations for the complainant's psychological injury affect legal decisions in a sexual harassment case

Research indicates that people engaged in legal decision-making use a host of biases and preconceptions to guide their decisions about whether the evidence presented to them is reasonable. However, few theories address how such expectations affect legal decision-makers. The present study attempted to determine if social judgment theory (SJT) can explain how and when legal decision-makers rely on expectations for the complainant's psychological injury in a hostile environment sexual harassment case. Two experiments provided undergraduate participants with a written summary of a hostile work environment allegation that first manipulated participants' expectations about reasonable psychological injuries (mild v. severe), and then presented them with actual severity levels of psychological injury (ranging from minimal to extreme). Experiment 1 (N = 295) hypothesized and found that participants who expected severe injuries perceived a greater range of psychological injuries to be reasonable than participants expecting mild injury. Experiment 2 ( N = 202) used similar methodology and investigated whether perceived reasonableness for the injury allegations affected legal decisions. Experiment 2 hypothesized that participants expecting severe psychological injury should render more pro-complainant decisions than participants expecting mild psychological injury. This result should be most pronounced when participants receive a moderate injury allegation, since this allegation was perceived as reasonable by participants expecting severe injury, but unreasonable by participants expecting mild injury. Consistent with SJT, participants who received a moderate injury but expected a severe injury found more liability than participants who received a moderate injury but expected a mild injury. Inconsistent with SJT, participants' expectations did not affect their compensatory damage decisions. In fact, more severe injury allegations increased damage awards regardless of participants' expectations. Although the results provide mixed support for applying SJT to legal decisions in sexual harassment cases, they emphasize the continuing role of oft-unstudied extra-legal factors (juror's expectations and psychological injury severity) on legal decisions.

Student Expositions as an Opportunity to Feel Proud: One Antidote to Expectations of Failure in Zone Schools

Expositions of student work at the end of the extended school year are one of many reform efforts in a specially formed School Improvement Zone in Miami Dade schools. This descriptive analysis offers examples of successful attempts to engender pride even in the face of formidable social and cultural obstacles.

Strategic Directions of Hotel Industry Expectations

A factor analysis is presented which indicates that among 20 potential strategic issues reated by hotl industry executives three fundamental strategic directions exist. The author summarizes an empiracle study that queried these individuals' beliefs regarding strategic issues they rated at most important.

Senior Savvy: Mature Diner's Restaurant Service Expectations

This article is a reflection of a study conducted with active mature consumers who enjoy dining out, traveling, and patronizing the service industry in general. The goal was to discover their restaurant service expectations in order to provide restaurateurs, hoteliers, educators, and students of hospitality management programs information about this important customer segment so that future plans for improving service would include considerations of their service needs.

An Autoregressive Conditional Filtering Process to remove Intraday Seasonal Volatility and its Application to Testing the Noisy Rational Expectations Model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.