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Although less than 1% of violent student deaths take place in schools, incidents such as the shootings that took place at Columbine High School in 1999 have fueled a general impression that schools are unsafe (Hall & Marsh, 2003; Osher & Quinn, 2003). Media reports about bomb threats, bullying episodes, and disruptive classroom behaviors have further contributed to a widespread belief that schools are not as safe as they should be (Osher & Quinn, 2003; Chicago Tribune Online Edition, 2006).

The purpose of this paper is to show that cafeteria style grading actually provides a course structure which encourages students to go beyond expectations.

Three instructors offered a total of 13 sections of a general education science class called “Fundamentals of Technology” from January 2012 to December 2013 using a cafeteria-style grading method. This means students get to choose to do those assignments, quizzes or tests that appeal to their own learning interests or styles and do not need to complete all the assignments to get an A grade. Rather, they complete those assignments desired in order to earn the applicable points. This paper researches the combined results of over 400 students to assess the success of cafeteria style grading.

These instructors found that half the students overall obtain an A grade and 9 percent of all students actually go above and beyond the requirements of an A grade by at least 5 percent. Actually, about 4 percent of students complete more than is required by an additional 10 percent or more.

Cafeteria style grading is a little researched methodology for student assessment. The research shows that cafeteria style grading actually provides a course structure which encourages students to go beyond expectations.

To evaluate various designs for a quality assurance system to detect and control human errors in a national screening programme for diabetic retinopathy.

A computer simulation was performed of some possible ways of sampling the referral decisions made during grading and of different criteria for initiating more intensive QA investigations. The effectiveness of QA systems was assessed by the ability to detect a grader making occasional errors in referral.

Substantial QA sample sizes are needed to ensure against inappropriate failure to refer. Detection of a grader who failed to refer one in ten cases can be achieved with a probability of 0.58 using an annual sample size of 300 and 0.77 using a sample size of 500.

An unmasked verification of a sample of non‐referrals by a specialist is the most effective method of internal QA for the diabetic retinopathy screening programme. Preferential sampling of those with some degree of disease may improve the efficiency of the system.

The present study aims to demonstrate the application of newly developed combinative distance-based assessment (CODAS) approach for grading and selection of Tossa jute fibres, which possesses some unique features uncommon to other variants of multi-criteria decision-making (MCDM) method.

The CODAS method was used in this study to rank/grade ten candidate lots of Tossa fibres on the basis of six apposite jute fibre properties, namely, fibre defect, root content, fineness, strength, colour and density. These six fibre properties were considered as the six decision criteria, here, and they were assigned weights as determined previously by an earlier researcher using analytic hierarchy process. The grading of jute fibres was done based on a comprehensive single index known as the assessment scores (Hi), in descending order of magnitude.

Among the 10 Tossa jute lots, T2 was ranked 1 (top grade) because of the highest assessment score of 6.887, followed by T1 with Rank 2 (assessment score 1.830). Because of the least assessment score of −2.795, the candidate lot T4 was considered as the worst, and hence ranked 10. The overall ranking pattern given by the CODAS method was similar to the TOPSIS approach done by Ghosh and Das (2013). This study was supported by various sensitivity analyses to judge the efficacy of the present approach. No occurrence of rank reversal during the sensitivity analyses obviously corroborates the robustness and stability of the CODAS method.

Jute pricing is fixed solely by the quality for which grading of fibre is prerequisite. The traditional “Hand and Eye” method or Bureau of Indian Standards (BIS) system for jute grading is basically subjective assessment and need domain expertise. MCDM is reported as the most viable solution which gives due importance to the fibre parameters while grading the fibres based on a single index. The present study demonstrates the maiden application of CODAS to address the fibre grading problems for jute industries. This approach can also be extended to solve other decision problems of textile industry, in general.

CODAS is a recently developed exponent of MCDM. Uniqueness of the present study lies in the fact that this is the first ever application of CODAS in the domain of textile industry, in general, and jute industry, in particular. CODAS approach is very simple involving a few simple mathematical equations yet a potent tool of decision-making. This method possesses some features uncommon in other variants of MCDM. Moreover, the efficacy of CODAS method is investigated through various sensitivity analyses, which has been ignored in the earlier approaches.

Cotton fibre lots are graded and selected for yarn spinning based on their quality value which is a function of certain fibre properties. Cotton grading and selection has created a domain of emerging interest among the researchers. Several researchers have addressed the said issue using a few exponents of multi-criteria decision-making (MCDM) technique. The purpose of this study is to demonstrate a cotton selection problem using a recently developed measurement of alternatives and ranking according to compromise solution (MARCOS) method which can handle almost any decision problem involving a finite number of alternatives and multiple conflicting decision criteria.

The MARCOS method of the MCDM technique was deployed in this study to rank 17 cotton fibre lots based on their quality values. Six apposite fibre properties, namely, fibre bundle strength, elongation, fineness, upper half mean length, uniformity index and short fibre content are considered as the six decision criteria assigning weights previously determined by an earlier researcher using analytic hierarchy process.

Among the 17 alternatives, C9 secured rank 1 (the best lot) with the highest utility function (0.704) and C7 occupied rank 17 (the worst lot) with the lowest utility function (0.596). Ranking given by MARCOS method showed high degree of congruence with the earlier approaches, as evidenced by high rank correlation coefficients (Rs > 0.814). During sensitivity analyses, no occurrence of rank reversal is observed. The correlations between the quality value-based ranking and the yarn tenacity-based rankings are better than many of the traditional methods. The results can be improved further by adopting other efficient method of weighting the criteria.

The properties of raw cotton have significant impact on the quality of final yarn. Compared to the traditional methods, MCDM is reported as the most viable solution in which fibre parameters are given their due importance while formulating a single index known as quality value. The present study demonstrates the application of a recently developed exponent of MCDM in the name of MARCOS for the first time to address a cotton fibre selection problem for textile spinning mills. The same approach can also be extended to solve other decision problems of the textile industry, in general.

Novelty of the present study lies in the fact that the MARCOS is a very recently developed MCDM method, and this is a maiden application of the MARCOS method in the domain of textile, in general, and cotton industry, in particular. The approach is very simple, highly effective and quite flexible in terms of number of alternatives and decision criteria, although highly robust and stable.

The Equal Pay Act 1970 (which came into operation on 29 December 1975) provides for an “equality clause” to be written into all contracts of employment. S.1(2) (a) of the 1970 Act (which has been amended by the Sex Discrimination Act 1975) provides:

Due to several unique characteristics, such as high tensile strength, low extensibility, high frictional resistance, biodegradability, eco-friendliness and cheapness, Jute ranks second just after cotton with respect to its worldwide consumption and production. To overcome the difficulties of the existing Jute grading procedure, this paper aims to focus on the application of decision-making trial and evaluation laboratory (DEMATEL) and multi-attributive border approximation area comparison (MABAC) methods for evaluation of 10 Tossa Jute fiber lots based on strength, defects, root content, color, fineness and bulk density properties.

The DEMATEL method divides all the six physical properties of Jute fiber into cause and effect groups. The most influencing property is also identified. On the other hand, the considered Jute fiber lots are ranked using MABAC method along with the identification of the strengths and weaknesses of each of them.

This combined approach would provide a more scientific and realistic way of Jute grading and evaluation based on various properties of the considered Jute fiber lots. The positions of the superior and the inferior Jute lots perfectly match with those as identified by the earlier researchers.

It is concluded that the adopted combined decision-making tool can be effectively applied for grading and evaluation of other natural fibers with diverse heterogeneous physical properties.

In spinning industries, selection of the most appropriate fibre for yarn manufacturing plays an important role for achieving an optimal mix of several yarn characteristics, like maximum tenacity, elasticity and spinning ability; and minimum unevenness and hairiness. Identification of the best suited cotton fibre from a set of available alternatives in presence of different conflicting physical properties is often treated as a multi-criteria decision-making (MCDM) problem. The paper aims to discuss this issue.

In this paper, the preference ranking organisation method for enrichment of evaluations (PROMETHEE) and geometrical analysis for interactive aid (GAIA) methods are integrated to solve a cotton fibre selection problem. The PROMETHEE II method ranks the alternative cotton fibres based on their net outranking flows, whereas GAIA acts as a visual aid to strongly support the derived selection decision. The weight stability intervals for all the considered fibre properties (criteria) over which the position of the top-ranked cotton fibre remains unchanged are also determined.

The clusters of cotton fibres formed in the developed GAIA plane act as a yard stick for their appropriate grading to aid the blending process. The ranking of 17 cotton fibres as achieved applying the combined PROMETHEE-GAIA approach highly corroborates with the observations of the past researchers which proves its immense potentiality and applicability in solving fibre selection problems.

Two MCDM methods in the form of PROMETHEE II and GAIA are integrated to provide a holistic approach for cotton fibre grading and selection while taking into consideration all the available cotton fibre properties.

Quality assessment of textile products is of prime concern to intimately meet consumer demands. The dilemma faced by textile producers is to figure out the stability among quality criteria and efficiently deal with target specifications. Hence, the basic devotion is to attain the optimum value product which entirely satisfies the views and perceptions of consumers. Selection of best fabric among several alternatives in the presence of contradictory measures is a disputing problem in multicriteria decision-making.

In the current study, the analytic hierarchy process (AHP) and preference ranking organization method for enrichment evaluation (PROMETHEE) are proficiently used to solve the problem in selection of branded woven shawls. AHP method verifies comparative weights of the criteria selection, while the ranking of fabric alternatives grounded on specific net-outranking flows is executed through PROMETHEE II method.

The collective AHP and PROMETHEE approaches are applied for the useful accomplishment of grading of branded shawls based on multicriteria weights, used for effective selection of fabric materials in the textile market.

In the apparel industry, fabric and garment manufacturers often rely on hit-and-trial methods, leading to significant wastage of valuable resources and time, in achieving the desirable fabric qualities. The implementation of the findings can assist apparel manufacturers in streamlining their fabric selection processes based on multiple criteria. By adopting this method, industry players can make informed decisions, ensuring a balance between quality standards and consumer expectations, thereby enhancing both product value and market competitiveness.

The methods of Visual PROMETHEE and AHP are assimilated to offer a complete method for the selection and grading of fabrics with reference to multiple selection criteria.

Performance appraisal based on a forced distribution system (FDS) is widely used in large corporate sectors around the globe. Though many researchers have pointed out several drawbacks in FDS, due to the absence of any suitable alternative, it has been (and continues to be) adopted by many industries over a long period of time. The purpose of this paper is to point out some serious limitations of this system and propose a simple modification to overcome these limitations.

FDS determines the relative positions of the employees involved in similar work by comparing them against one another, and based on their performance, the employees receive different grades. Here the authors use the Likert's scaling method to convert these grades into numerical scores, then these scores are used to estimate the average performance of each group of employees, which is referred to as the group index. Taking these group indices into consideration, the authors propose a modified performance score of each employee for their final evaluation. Efficiencies of the existing FDS and the proposed modified version are compared using a simple measure of rank correlation known as the Kendall's tau‐statistic.

Extensive simulation studies show that the modified algorithm is uniformly better than the existing one over different schemes for allocations of employees to different projects, and depending on the allocation scheme, it can lead to substantial improvement.

This paper can be considered as the first to mathematically demonstrate the problems lying in the appraisal system based on a forced distribution and the first that provides a simple but effective solution which can be adopted by the organizations using FDS for performance appraisal.