Coefficient Of Alienation Research Articles

Leisure education in schools: challenges, choices and consequences

ABSTRACTDespite the growing advocacy for implementing leisure education in schools, its application lags behind its global expectations. Unlike the US trend of “back to basics” educational philosophy which prioritizes the learning of core subjects over leisure related subjects, countries in Asia have been changing their curricula to nurture the whole person development and thus paving the way for infusing leisure education into school systems. One example is Hong Kong which has undergone a major education reform in the last two decades. Even though scholars have suggested numerous channels and strategies for leisure education in schools, a lucid framework which takes into account the views of those for which leisure education in planned was not developed. This study is to explore the underlying dimensions of leisure education as it is manifested by teachers’ and students’ views. A Seventeen-item questionnaire has been submitted to 105 teachers and 1187 students from seven schools geographically distributed around Hong Kong. Responses were analyzed through Smallest Space Analysis (SSA). The SSA solutions among both students and teachers have yield three-dimensional solution with coefficient of alienation .14. The solutions indicated a division to five dimensions: values and attitudes, self-development, motivation, ends and means and education among teachers and three combined dimensions among students: motivation and ends and means, self-motivation and education which includes active engagement, and values and attitudes. The identified dimensions resonate well with the suggested channels and strategies for leisure education in schools which incorporate various offerings, freedom of choice, trial and error and experiential learning. Whereas this similarity could facilitate the utilization of leisure education in schools, there is a need to consider the nature, strategy and context of such implementation. The paper addresses these challenges and draws implications for teacher training, parent education and continued advocacy for the right for leisure and its significance for whole person development.

Multi-dimensional Perception of Parental Involvement

The main purpose of this study was to define and conceptualize the term parental involvement. A questionnaire was administrated to parents (140), teachers (145), students (120) and high ranking civil servants in the Ministry of Education (30). Responses were analyzed through Smallest Space Analysis (SSA). The SSA solution among all groups rendered a two dimensional solution with a coefficient of alienation .18. The SSA map clearly divided 44 parental activities into four quadrants. The left and right regents represent the focus of parental activity: The left regent represents in-school activities and the right side represents out-school activities. The upper and lower regents represent the organizational level: The upper regent represents organizational based activities and the lower regent represents student-based activities. The initial findings also demonstrated that parental involvement can be defined by the 44 actions, which are deployed on the SSA map in a polarized facet. The facet includes four elements (separation index 1.00): Resources, school welfare, control processes and pedagogical and wellbeing contents. We now have a better understanding of what constitutes school-related parental involvement; we know that it reflects a broad spectrum of parental actions and activities, which can take place either at school or outside the school. The involvement can be expressed actively or passively, often relating to the school as an organization and often in the personal context of one's own child.

Pollen Grain Proportions as a Paleoecological Reconstruction Tool: The Correlativity of Zonocostites Ramonae and Monoporites Annulatus in the Niger Delta Basin as a Case Study

Zonocostites ramonae and Monoporites annulatus are the most abundant pollen in each of the wells M-1, 2 and 3. They constitute 82.4%, 90.0% and 91.5% of the total pollen respectively. The proportionality of the two taxa was considered for predicting the prevailing paleoecological condition during the deposition of sediments in the studied wells. The mean values of Z. ramonae in the wells were 88.8, 269 and 169 respectively; that of M. annulatus were 5.76, 11.7 and 16.1. The correlation coefficient (rc) were 0.634, 0.666 and 0.189 respectively whilst the regression coefficient values were -0.883, 6.16 and 14.7. The coefficient of variation percent (CV%) were 52.3, 298 and 259 respectively for Z. ramonae and 107, 77.3 and 72.7 respectively for M. annulatus. The coefficient of alienation and index of forecasting efficiency ranged from 0.746 to 0.982 and 0.018 to 0.254 respectively. The percentage of the difference in the occurrence of the two taxa varied greatly; there were five samples with 100%, 96 dominated with >50.0% and one of the remaining two samples had a negative value whilst the other had 0.00%. The correlation coefficient indicated that the occurrence of Z. ramonae and M. annulatus in M-1 and M-2 was very significantly different but not significantly different in M-3 at rc = 0.05. The cross correlation between Z. ramonae and M. annulatus showed that both spectra were generally not coherent which meant that these taxa only slightly shared their source area. This work inferred that whilst Z. ramonae always suggested a mangrove environment, however, using M. annulatus as a simple indicator of arid condition may overstate trends or boundary transitions and also disregard seasonal variation in swamp communities. Predicting the relationship of occurrence in these taxa might be difficult since the reduction in the error of prediction (IFE) ranged from low to very low (0.226, 0.254, 0.018).

Nutritional values of the lipid composition of the free-range chicken eggs

Poultry eggs are eaten in most areas of the world with fewer social taboos associated with them than pigs and cattle. The most commonly used bird eggs are those from chicken. In Nigeria, the domestic foul dominates the poultry industry. Of the 120 million indigenous poultry population in Nigeria, the domestic fowl constitutes about 91 % of this. For this reason, the present work tried to evaluate the nutritional levels of the lipid composition of the free-range fertilized cooked chicken eggs. Five eggs were involved in the study and they were collected at once. The following experimental procedures were carried out on the yolk and the albumen using standard analytical methods: crude fat determination, preparation of methyl esters and fatty acid analysis. Also determined was the quality assurance of the determinations to ensure their accuracies, calculation of uncertainty interval percentage (UIP) particularly for the fatty acid values. Statistical evaluations carried out included: linear correlation coefficient (rxy), coefficient of determination (rxy 2 ), linear regression coefficient (Rxy), coefficient of alienation (CA) and index of forecasting efficiency (IFE). The study reports the nutritional values of the lipid composition of the free-range chicken eggs analyzing separately the yolk and the albumen. The yolk was 32.8 % of the total egg weight while the albumen was 53.8 %. The total crude fat in yolk was 22.9 g/100 g whilst it was 0.001 g/100 g in albumen. The total fatty acid in yolk was 19.0 g/100 g; it was 0.00083 g/100 g in albumen. The SFA level was 35.0 % in total fatty acids in yolk; it was 31.8 % in albumen. Total monounsaturated fatty acids (MUFA) in yolk was 43.5 % but 42.9 % in albumen. Total n-6 PUFA was 21.8 % in yolk and 25.2 % in albumen. The PUFA/SFA was 0.62 in yolk and 0.79 in albumen. Lecithin was high in yolk [115 mg/100 g; 46.0 %] but at trace level [23.3e-3 mg/100 g; 63.1 %] in albumen. Sterol was not detected in the albumen but total sterol in the yolk was 386 mg/100 g having cholesterol level of 86.3 mg/100 g (22.4 %). The levels of MUFA + PUFA in yolk was 65.3 % and 68.1 % in albumen showing that the chicken egg could be classified as being made up majorly of unsaturated oil. Free-range laying hens are given outdoor access instead of being contained in crowded cages; this gives them wide range of various feeding opportunities. This report showed the free-range chicken eggs yolk to be far more concentrated in crude fat; total fatty acids; SFA; MUFA; n-6 PUFA; high PUFA/SFA; high lecithin; high cephalin; high stigmasterol and cholesterol than the corresponding albumen. The cholesterol level was also below the average recommended level.

A taxonomy and comparison of computer security incidents from the commercial and government sectors

Cyber incidents are growing in intensity and severity. Several industry groups are therefore taking steps to better coordinate and improve information security across sectors. Also, various different types of public–private partnerships are developing, where cyber incident information is shared across institutions. This cooperation may improve the understanding of various types of cyber incidents, their severity, and impact on various types of targets. Research has shown that different types of attackers may be distinguished in terms of sophistication, skill level, attacking style, and objective of attack. It may further be proposed that different sectors experience different types of attacks. Attack characteristics and information about the modus operandi of criminal offenders have been used to learn more about the attacker and the motive of an attack. This information may also be used to distinguish between cyber attacks towards different types of targets. The current study focuses on reported cyber intrusions by the commercial and government sectors. The reported data come from CERT ®Coordination Center (CERT/CC), which has categorized the aspects of cyber intrusions in the current study. The aspects analyzed are: ‘Method of Operation (MO)’ which refers to the methods used by perpetrator to carry out an attack; ‘Impact’ which refers to the effect of the attack; ‘Source’ which refers to the source of the attack, and ‘Target’ which refers to the victim of the attack. The current study uses 839 cases of cyber attacks towards the commercial sector and 558 cases towards the government sector. The 23 variables from the four different cyber intrusion aspects; MO, impact, source sector and target sector, were analyzed using multidimensional scaling (MDS), which is a technique that has often been used when profiling traditional types of crimes. The analysis gave a Guttman–Lingoes' coefficient of alienation of 0.19 with 42 iterations in a 3-dimensional solution. It was shown that the commercial and government sectors experience different types of attacks, with different types of impact, stemming from different sources. The findings and implications are discussed in relation to the benefits of standardization, reporting, and sharing of cyber incident information.

The Correlation Coefficient: An Overview

Correlation and regression are different, but not mutually exclusive, techniques. Roughly, regression is used for prediction (which does not extrapolate beyond the data used in the analysis) whereas correlation is used to determine the degree of association. There situations in which the x variable is not fixed or readily chosen by the experimenter, but instead is a random covariate to the y variable. This paper shows the relationships between the coefficient of determination, the multiple correlation coefficient, the covariance, the correlation coefficient and the coefficient of alienation, for the case of two related variables x and y. It discusses the uses of the correlation coefficient r, either as a way to infer correlation, or to test linearity. A number of graphical examples are provided as well as examples of actual chemical applications. The paper recommends the use of z Fisher transformation instead of r values because r is not normally distributed but z is (at least in approximation). For either correlation or for regression models, the same expressions are valid, although they differ significantly in meaning.

Long term effect of municipal waste disposal on soil properties and productivity of sites used for urban agriculture in Abakaliki, Nigeria

An assessment on the impact of long term (20 years) municipal waste disposal on soil physicochemical properties and soil productivity in municipal waste dump sites was carried out in urban Abakaliki, southeastern Nigeria. Profile pits were dug at selected points and auger and core samples were collected from different soil horizons of dump and non-dump sites using free survey technique to choose observation points. There were differences in particle size distribution between dump and non-dump sites. Similarly, soil bulk density was lower by 9–13% while total porosity and hydraulic conductivity were higher by 9–14% and 240–463%, respectively, in the dump site relative to non-dump sites. Soil organic matter, total nitrogen, cation exchange capacity (CEC) and percent base saturation increased from 701 to 743, 646 to 740, 7% to 10% and 5% to 14%, respectively, in the dump site soil relative to non-dump site soil. These results were confirmed by a high coefficient of alienation (degree of unrelatedness, 1−R 2 ) in bulk density, 0.65; total porosity, 0.58; hydraulic conductivity, 0.87; organic matter, 0.93; total N, 0.82; pH, 0.85 and cation exchange capacity, 0.97 between dump and non-dump soils. Heavy metals (Pb, Cu, Fe and Zn) increased by between 214% and 2040% in dump site soils relative to non-dump site soil. This may lead to increased uptake of metals by some test crops although their transfer ratios differ from crop to crop. Long term dumping of municipal wastes can influence soil properties and productivity at municipal waste dump sites but still may be used for farming provided that ecotoxological risks associated with its usage are continuously assessed and controlled.

Models of human exposure based on environmental monitoring

The relevant exposure to environmental pollutants or relevant confounders can virtually never be measured directly in sufficient detail in a sufficient number of people included in an epidemiological study. Instead, surrogate indicators of exposure are used that are implicitly or explicitly linked by (conceptual) models to the ‘relevant exposure’. Using specified indices (e.g., the coefficient of alienation and forecasting efficiency), the models of different forms can be compared and tested in special investigations. This can evaluate the criterion validity of the model through analysis of the agreement between the model estimates, based on measured surrogate indicators of the exposure, and the actual exposure. The perspective on the construct under study may further change the validity of the exposure indicator. Therefore, sub-studies evaluating the quality of exposure indicators should be considered as integral part of any study in environmental epidemiology, preferably as a pre-study or pilot study.

Measures of Asociation between vectors

Let be a (p+q) - variate random vector (p≧1, q≧1) with . Partition ∑into p- and q- rows and columns such that . Let be the nonzero characteristic roots of where s is the rank of ∑12. Based on those roots, a class measures of association between is characterised. Some basic properties of these measures are explored. Among various special cases, an attractive measure of association is favoured which is derived from the vector coefficient of alienation. Justification fof the use of such a measure is included.

A Short-Cut Measure of Correlation

B EGINNING with a scatter diagram and regression curve, this method provides a quick graphic estimate of the coefficient or index of simple correlation. This is done by measuring the ranges about the regression curve and about the mean of the dependent variable, respectively, that include two-thirds of the items. The ratio of these values is approximately the coefficient of alienation, from which the coefficient or index of correlation may be looked up in a table. This method appears to be reasonably accurate and quicker than other short-cut methods. It may also be used to illustrate the meaning of correlation for teaching purposes. 1

Twelve Tests That Have Proved Practical in Commerical Applications

It is the shared experience of many workers in the field of psychometrics that broadens and enhances the value of such scientific techniques. This brief writing represents an effort to share some six years of experience with the tests mentioned herein. It reflects the confidence of several workers in the field of industrial and commercial testing where the end-goal of the testing was the selection, placement, upgrading or training of employees. It is not suggested that other workers accept without question the experience described here. Rather, it is felt that the reader may devote effort to further validation with the knowledge that his effort is less likely to be wasted because of this experience of others. The paper includes no comment about the many tests that have been tried and which did not prove practical economically or from the point of view of validity. To condemn a test because it failed in one or a few situations is as unscientific as to over-estimate its value. We do not have a universal common denominator for test evaluation because each situation in which tests are used requires a compromise and the compromise itself is often more important than the basic nature of the instrument or instruments used. In small groups we must compromise between rigid statistical appraisal and obvious case analysis, in industry we must compromise between extreme accuracy and the practical element of costs, in guidance we must compromise between the coefficient of correlation and the coefficient of alienation thus keeping before ourselves the fact that we are dealing with the laws of chance rather than with immutable facts.

Expectancy Tables

The product moment correlation coefficient is commonly used by research workers as a statistical measure of the relationship between two measures of a group of individuals. In applied psychology this statistic is often used to define the correspondence between scores on tests or other measures of traits and apti tudes and a criterion of proficiency on a job, in a training course in school or industry, or some other activity. In this case the ultimate objective is to evaluate the criterion poten tialities of an individual or a group on the basis of other data. It is often desirable and sometimes neces sary to present the results of correlation anal ysis to the layman. However, the concept of correlation is difficult to interpret to the non technically trained person. In addition, the coefficient itself provides neither the techni cian nor the layman with a concrete evalua tive statement of the expected criterion per formance of individuals with given scores on the associated variable. Accordingly, a method is needed for reinterpreting correlation coeffi cients in terms of the predictive significance of the association expressed in terms of simple mathematical concepts which are uni versally understood.1 Taylor and Russell (4) have developed tables for interpreting certain correlation coefficients in terms of the proportion of the selected group who will be expected to be suc cessful if a given percent of the total group is considered successful on the basis of a mini mum criterion score and a given percent of the total group is selected on the basis of a minimum score on the predictor variable. This method has considerable merit for interpret ing the correlation coefficient in terms of its predictive significance if one is interested only 1 Various functions of the correlation coefficient such as the coefficient of alienation, k, the coefficient of forecasting effi ciency, E, and the coefficient of determination, r2, have been used to aid in the interpretation of the correlation coefficient but none of these are superior to the coefficient itself for these purposes. in group predictions and if it can be assumed that the correlation surface is normal. How

The reliability and validity of certain arithmetic tests

In studying the achievement of pupils in the elementary school it is important to know the reliability of our measuring instruments. It is obviously worth very little to measure school achievement and judge the merit of instruction thereby unless the reliability and validity of our measuring instruments are known. During the school year 1926-1927 the writers gave a number of arithmetic tests to the pupils of the sixth and seventh grades in the Peabody Demonstration School. The papers were each checked by two different persons so as to eliminate errors in scoring. When the scores were finally tabulated, it was found that seventy-three pupils had taken all the tests. The scores made by these pupils were accordingly taken for the purpose of this study. In handling the data the scores from the two grades were thrown together so as to somewhat lighten the statistical work. For several of the tests it was necessary to reduce the scores for the pupils of each grade to standard scores before this was done. Correlations were found between the different forms of the same test and between each test and a composite score. This composite score was secured by first converting all test scores into standard scores and then adding these for each pupil. By using this method each test received equal weight in the composite. This composite was used in finding the validity of each test. It is realized that there is a certain amount of self-correlation involved, and that this would tend to raise the size of the correlation. Also the fact that the scores from the two grades were thrown into one distribution would tend in most cases to raise the correlation. The correlation of one form of a test with another form of the same test was taken as a measure of reliability. Since several of the tests are not published in more than one form, it was necessary to repeat the same form in order to secure a measure of reliability. This was true in the case of the Courtis Arithmetic Test and the Cleveland Survey Arithmetic Tests. The coefficient of reliability and the coefficient of alienation are given in Table I for the several tests. The coefficient of reliability, as previously stated, was found by correlating one form of a test with