Family-Oriented Pre-Trial Intervention Essay Example for Free

Family-Oriented Pre-Trial Intervention Essay Pre-trial intervention (PTI) has been shown to be more effective when the family is involved in the process.   Most PTI programs focus on the treatment given before release from confinement.   Family-oriented PTI programs look beyond the prison set-up and attempt to establish a community for the accused to return to (Dembo, 2003). The reality is that the social stigma against persons released from prison facilities poses a strong hindrance against re-integration into the community efforts towards rehabilitation (Tate, Reppucci, Mulvey, 1995).   By conducting regular and in-depth discussions with the family regarding rehabilitation, the basic social support system of the accused is assured (Dembo, 2003). The present study will replicate a family-intervention system conducted by Dembo, Schmeidler, and Wothke (2003) wherein families were trained to address the rehabilitative process a family-member was undergoing with the end goal of improving PTI.   However, in the study conducted by Dembo et al., the dependent variable was measured through self-report data. The present research will use indicators of reintegration into society along with repeated delinquent acts to assess whether or not family-intervention is indeed a rehabilitative process.   The succeeding sections will reflect the design and method of the research.   The research questions to be answered by the present study will also be clarified in order to show a clear direction of the research being conducted. Research Questions   Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚   The present research will attempt to answer the question as to whether or not family-oriented pre-trial intervention programs improve rehabilitative efforts by increasing the incidence of community participation and integration as well as decreasing the incidence of delinquent behavior.   This question may be answered by looking into the activities engaged in by the offender upon release and with the introduction of family PTI.   The research has several hypotheses: 1.  Ã‚  Ã‚  Ã‚  Ã‚   That family PTI will increase community involvement; 2.  Ã‚  Ã‚  Ã‚  Ã‚   That family PTI will decrease delinquent behavior; and 3.  Ã‚  Ã‚  Ã‚  Ã‚   That family-oriented PTI programs are more effective in fostering rehabilitation than offender-centered PTI. Evaluation Population The main thrust of the research is to assess the efficacy of a proposed pre-trial intervention program.   A family-oriented program will thus be administered to one experimental group while a non-family-oriented program will be applied to another group.   These programs will be administered to one group of individuals and their families. By doing so, there will be greater parallelism in the comparison of the two programs.     Ã‚  Ã‚   Considering that the family set-up is most relevant in the case of minors, the present study will limit its population to juvenile delinquents (Alexander Parsons, 1973). In particular, this research will limit its population to minors still living with their parents.   In order to obtain a sufficient number of participants, several penal facilities will be asked for consent for the participation of their detained juvenile delinquents who have not yet started with their PTI programs.   This will control for confounding effects of other PTI programs which may be administered by the penal facility. Evaluation Design The design to be used in the present research is the experimental design.   The experimental design has been lauded as the most rigorous design.   It is essentially the gold standard of research designs because of its ability to isolate the independent variables being studied and their relationship with the dependent variables (Creswell, 2009). This is the most appropriate design for the research to be conducted because the juvenile delinquents who will give consent to participation in the experiment will be randomly assigned into two groups.   These two groups are the experimental and control groups.   Moreover, previous research has shown that rigorous methods provide the best results with respect to reduced recidivism in studies of juvenile delinquents (Latimer, 1999). The experimental and control groups will be identical in all regards except for the presence of family-intervention in the experimental group.   In both groups, the juvenile delinquent will undergo identical PTI processes wherein they will receive treatment and training regarding rehabilitative practices. However, in the first group there will be an added intervention wherein the researchers will actively foster a dialogue with the family of the juvenile delinquent in order to help them understand and cope with their child’s rehabilitation.   In order to assess whether changes have truly resulted, a pre-intervention assessment will be administered to the participants and their families.   After a period of six months the assessment will be administered again in order to track any changes in disposition and placement of the juvenile delinquents. Population and Sample The study will limit the number of participants to forty due to the longitudinal nature of the study and due to the need for in-depth counseling to be undertaken with the families involved.   Time and resource constraints would not support a study involving an experimental group of more than twenty families. The participants will be chosen primarily based on their prior reception of PTI treatment and the fact of residence with family members.   Demographic factors such age, gender, social status and family situation will be recorded and assessed but will not serve as criteria for acceptance into participation.   By doing so, the experiment retains a higher external validity.   However, the recording of these factors will broaden the discussion and interpretation of results as the effect these factors play on the rehabilitation of participants may emerge as serendipitous findings.

The Internet :: Exploratory Essays Research Papers

Introduction Welcome to a world beyond reality; a world full of problems, promise, and possibilities. You are now in hyperreality, virtual reality, or cyberspace. It is whatever you want it to be. "[T]he Internet is like a highway, feeding small communities and large cities, and connecting their loops, backroads and alleyways" (Estrada XU). In other words, the Internet is a network of networks-a web that connects a vast number of computers. Wait! Don't give up yet, it's easier than you think. Using the Internet isn't "rocket science". An area that was once only for researchers is now used by a wide range of people from elementary students to farmers. The internet is an interactive environment. In her book, The Internet Companion Plus, Tracy Laqey gives the difference between television and the Internet by saying that when it comes to television, "we are only the watchers, but with the Internet we are "the reporters, the viewers, and the production team" (3). The Internet has very few restrictions these days, so for the most part you are free to do and say whatever you choose. It is the value of what you say, not who you are, that gets people to listen. The Internet is an "open and sharing environment" (3), as well as a complicated environment. With every involved endeavor a certain amount of information is required to fully enjoy and benefit from the experience. As for the Internet, this information is at first overwhelming. Let's put aside the details of connecting the systems and the technicalities and concentrate on the actual usage of the web. The internet has made our lives easier through ingenious inventions like computeriz ed card catalogs and e-mail. But, in order to fully understand this huge system, we must first know where it came from. The Internet had a modest start as ARPANET, a U.S. Defense Department network, and was designed to withstand a nuclear bomb attack. Information could be put in many different places to avoid a centralized storage of information. It was later split into two networks, and from one of these networks the Internet was born. Today the Internet has evolved into a monster. In their book, The Mosaic Handbook, Dale Dougherty, Richard Koman, and Paula Ferguson describe the Internet as "a cultural icon . . . [it] has come to represent what the future looks like today" (2). The possibilities are endless, and although we won't list them all here, we will introduce a few.

Chapter 6 – Planning Capacity

chapter 6: Planning capacity Capacity the maximum rate of output of a process or a system. Acquisition of new capacity requires extensive planning, and often involves significant expenditure of resources and time. Capacity decisions must be made in light of several long-term issues such as the firm’s economies and diseconomies of scale, capacity cushions, timing and sizing strategies, and trade-offs between customer service and capacity utilization. Planning capacity across the organizationAccounting provide cost information needed to evaluate capacity expansion Finance financial analysis of proposed capacity expansion investments and raises funds Marketing demand forecasts needed to identify capacity gaps. Operations selection of capacity strategies that can be implemented to effectively meet future demand. Human Resources hiring and training employees needed to support internal capacity plans. planning long-term capacity When choosing a capacity strategy: How much of a cushi on is needed to handle variable or uncertain demand? Should we expand capacity ahead of demand, or wait until demand is more certain? easures of capacity and utilization Output Measures Are best utilized when applied to individual processes within the firm, or when the firm provides a relatively small number of standardized services and products. For example, a car manufacturing plant may measure capacity in terms of the number of cars produced per day. Inputs Measures Are used for low-volume, flexible processes (custom products). For example a custom furniture maker might measure capacity in terms of inputs such as number of workstations or number of workers. The problem of input measures is that demand is expressed as an output rate.If the furniture maker wants to keep up with demand, he must convert the business’s annual demand for furniture into labor hours and number of employees required to fulfill those hours. Utilization Degree to which a resource (equipment, space, w orker) is currently being used. Utilization= Average Output RateMaximum Capacityx 100% The numerator and the denominator should be measured in the same units. A process can be operated above the 100%, with overtime, extra shifts, overstaffing, subcontracting, etc, but this is not sustainable for long. Economies of scaleEconomies of scale The average unit cost of a service or good can be reduced by increasing its output rate. Why? * Spreading fixed costs same fixed costs divided by more units * Reducing construction costs doubling the size of the facility usually doesn’t double construction costs (building permits, architect’s fees, rental) * Cutting costs of purchased materials better bargaining position and quantity discounts * Finding process advantages speed up the learning effect, lowering inventory, improving process and job designs, and reducing the number of changeovers. diseconomies of scaleDiseconomies of scale The average cost per unit increases as the facili ty’s size increases. The reason is that excessive size can bring complexity, loss of focus, and inefficiencies. capacity timing and sizing strategies sizing capacity cushions Capacity cushion=100%-Average Utilization rate (%) When the average utilization rate approaches 100% for long periods, it’s a signal to increase capacity or decrease order acceptance to avoid declining productivity. The optimal capacity cushion depends on the industry. Particularly, in front-office processes where customers expect fast service times, large cushions are vital (more variable demand).For capital-intensive firms, minimizing the capacity cushion is vital (unused capacity costs money). timing and sizing expansion Two strategies: * Expansionist strategy large, infrequent jumps in capacity. Is ahead of demand, and minimizes the chance of sales lost to insufficient capacity * Wait-and-see strategy smaller, more frequent jumps. It lags behind demand. To meet any shortfalls, it relies on sho rt-term operations (overtime, temporary workers, subcontractors, postponement of preventive maintenance on equipment).It reduces the risk of overexpansion based on overly optimistic demand forecasts, obsolete technology, or inaccurate assumptions regarding the competition. This strategy fits the short-term outlook but can erode market share over the long run. Timing and sizing of expansion are related: if demand is increasing and the time between increments increases, the size of the increments must also increase. An intermediate strategy can be â€Å"follow the leader†, so nobody gains a competitive advantage for being ahead of demand, and everyone shares the agony of overcapacity in the other case. inking capacity and other decisions Capacity cushions in the long run buffer the organization against uncertainty, as do resource flexibility, inventory, and longer customer lead times. If a change is made in any one decision area, the capacity cushion may also need to be changed to compensate. For example: Lower volume of production (more capacity cushion) to raise prices or vice versa. a systematic approach to long-term capacity decisions 4 steps: 1. Estimate future capacity requirements 2. Identify gaps by comparing requirements with available capacity 3. Develop alternative plans for reducing the gaps . Evaluate each alternative, both qualitatively and quantitatively, and make a final choice step 1: estimate capacity requirements A process’s capacity requirement is what its capacity should be for some future time period to meet the demand of the firm’s customers (external or internal), given the firm’s desired capacity cushion. Larger requirements are practical for processes or workstations that could potentially be bottlenecks in the future, and management may even plan for longer cushions than normal. Capacity requirements can be expressed in: * Output measure * Input measureEither way, the foundation for the estimate is forecasts of demand, productivity, competition, and technological change. The further ahead you look, the more chance you have of making an inaccurate forecast. Using output measures Demand forecasts for future years are used as a basis for extrapolating capacity requirements into the future. If demand is expected to double in the next 5 years, then the capacity requirements also double. For example: Actual demand 50 customers per day; expected demand = 100 customers per day; desirable cushion = 20%. So capacity should be (100)/(1-0. )=125 customers per day. Using input measures Output measures may be insufficient in these situations: * Product variety and process divergence is high (customized products) * The product or service mix is changing * Productivity rates are expected to change * Significant learning effects are expected In these cases, an input measure should be used (number of employees, machines, trucks, etc) One product processed When just one service or product is processed at an operation and the time period is a particular year, the capacity requirement (M) is: M=DpN[1-C100]D=demand forecast for the year (number of customers served or units produced) p=processing time (in hours per costumer served or unit produced) N=Total number of hours per year during which the process operates C=desired capacity cushion (expressed as a percent) M=number of input units required and should be calculated for each year in the time horizon Many products processed Setup time time required to change a process or an operation from making one service or product to making another. To calculate the total setup time D/Q*s Where D=demand forecast for the yearQ= number of units processed between setups s= time per setup For example, if the demand is 1200 units, and the average lot size is 100, there are 1200/100=12 setups per year. Accounting for both processing and setup times for multiple products, we get: M=[Dp+DQs]product 1+[Dp+DQs]product 2+†¦+[Dp+DQs]product nN[1-C100 ] When â€Å"M† is not an integer and we are talking about number of machines, you can round up the fractional part, unless it is cost efficient to use short-term options, such as overtime or stockouts.But if we are talking about number of employees and we get 23. 6, we can use 23 employees and use a little overtime (in this case, 60% of a full-time person). step 2: identify gaps A capacity gap is any difference (positive or negative) between projected capacity requirements (M) and current capacity. step 3: develop alternatives Develop alternative plans to cope with projected gaps. One alternative is the base case do nothing and simply lose orders from any demand that exceeds current capacity or incur costs because capacity is too large.Other alternatives: various timing and sizing options (expansionist or wait-and-see strategies); expanding at a different location; and using short term options. For reducing capacity, the alternatives include closing plants, laying off employ ees, reducing days or hours of operations. step 4: evaluate the alternatives Evaluate qualitatively and quantitatively. Qualitative concerns The manager looks at how each alternative fits the overall capacity strategy and other aspects of the business not covered by the financial analysis (uncertainties about demand, competitive reaction, technological change, and cost estimates).Some of these factors can’t be quantified and must be assessed on the basis of judgment and experience. Quantitative concerns The manager estimates the change in cash flows for each alternative over the forecast time horizon compared to the base case. tools for capacity planning waiting-line models Are useful in high customer-contact processes. Waiting-line models use probability distributions to provide estimates of average customer wait time, average length of waiting lines, and utilization of the work center.Managers can use this information to choose the most cost-effective capacity, balancing cu stomer service and the cost of adding capacity. This topic will be treated more deeply in the appendix (siguiente resumen) simulation Simulations can identify the process’s bottlenecks and appropriate capacity cushions, even for complex processes with random demand patterns and predictable flows in demand during a typical day. decision trees A decision tree can be particularly valuable for evaluating different capacity extension alternatives when demand is uncertain and sequential decisions are involved.

Illinois State University Acceptance Rate, SAT/ACT Scores, GPA

Illinois State University is a public university with an acceptance rate of 89%. Established in 1857, Illinois State University is the oldest public university in the state of Illinois. The campus is located in Normal, a small city less than three hours from Chicago, St. Louis, and Indianapolis. The university has broad academic strengths, and programs in business, education, and nursing are all highly regarded nationally. Students can choose from more than 200 academic majors and minors. Classes are supported by a 19-to-1  student/faculty ratio, and about two-thirds of classes have fewer than 30 students. In athletics, the Illinois State Redbirds compete in the NCAA Division I  Missouri Valley Conference. The university fields 17 Division I teams. Considering applying to Illinois State University? Here are the admissions statistics you should know, including average SAT/ACT scores and GPAs of admitted students. Acceptance Rate During the 2017-18 admissions cycle, Illinois State University had an acceptance rate of 89%. This means that for every 100 students who applied, 89 students were admitted, making Illinois States admissions process somewhat less competitive. Admissions Statistics (2017-18) Number of Applicants 12,886 Percent Admitted 89% Percent Admitted Who Enrolled (Yield) 32% SAT Scores and Requirements Illinois State University requires that all applicants submit either SAT or ACT scores. During the 2017-18 admissions cycle, 70% of admitted students submitted SAT scores. SAT Range (Admitted Students) Section 25th Percentile 75th Percentile ERW 510 600 Math 500 590 ERW=Evidence-Based Reading and Writing This admissions data tells us that most of Illinois States admitted students fall within the top 35% nationally on the SAT. For the evidence-based reading and writing section, 50% of students admitted to Illinois State scored between 510 and 600, while 25% scored below 510 and 25% scored above 600. On the math section, 50% of admitted students scored between 500 and 590, while 25% scored below 500 and 25% scored above 590. Applicants with a composite SAT score of 1190 or higher will be particularly competitive for Illinois State. Requirements Illinois State University does not require the SAT writing section for admission. Note that Illinois State does not superscore the SAT; the admissions office will consider your highest composite score from a single sitting. ACT Scores and Requirements Illinois State requires that all applicants submit either SAT or ACT scores. During the 2017-18 admissions cycle, 58% of admitted students submitted ACT scores. ACT Range (Admitted Students) Section 25th Percentile 75th Percentile English 20 26 Math 19 26 Composite 20 26 This admissions data tells us that most of Illinois States admitted students fall within the top 49% nationally on the ACT. The middle 50% of students admitted to Illinois State received a composite ACT score between 20 and 26, while 25% scored above 26 and 25% scored below 20. Requirements Note that Illinois State does not superscore ACT results; your highest composite ACT score will be considered. Illinois State does not require the ACT writing section. GPA In 2018, the average high school GPA of Illinois States incoming freshmen class was 3.39, and over 58% of students had average GPAs of 3.25 and above. These results suggest that most successful applicants to Illinois State University have primarily B grades. Self-Reported GPA/SAT/ACT Graph Illinois State University Applicants Self-Reported GPA/SAT/ACT Graph. Data courtesy of Cappex. The admissions data in the graph is self-reported by applicants to Illinois State University. GPAs are unweighted. Find out how you compare to accepted students, see the real-time graph, and calculate your chances of getting in  with a free Cappex account. Admissions Chances Illinois State University, which accepts 89% of applicants, has a slightly selective admissions process. If your SAT/ACT scores and GPA fall within the schools average ranges, you have a strong chance of being accepted. Illinois State also requires that applicants complete a core high school curriculum including 4 years of English, 3 years of math, 2 years of natural science (including labs), 2 years of social science, and 2 years of foreign language or fine arts. Applicants with the strongest academic records have the best chance of admission. Note that some programs at Illinois State are more selective than others. Students with borderline grades or test scores are encouraged to submit an optional academic personal statement to explain their academic performance. In the graph above, the blue and green dots represent accepted students, and most of them had a high school average of B- or higher, an ACT composite score of 18 or higher, and a combined SAT score (ERWM) of at least 950. An applicants chances for admission increase measurably with grades and test scores above these lower ranges. If You Like Illinois State University, You May Also Like These Schools Michigan State UniversityUniversity of MissouriPurdue UniversityIndiana University - BloomingtonNorthwestern UniversityOhio State University All admissions data has been sourced from the National Center for Education Statistics and Illinois State University Undergraduate Admissions Office.