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n this study, time series data has been related to broad agricultural outputs which included farming, livestock, forestry, and fisheries and 3 conventional inputs: labour, land, and capital, to construct an index of total factor productivity (TFP) between 1969-70 to 2005-06. A TFP index is simply the ratio of an output index to an input index. Therefore, growth in TFP is the residual share of output growth after accounting for changes in land, labor, and other conventional agricultural inputs. Changes in TFP can be interpreted as a measure of the collective contribution of non-conventional inputs in agriculture, such as improvements in input quality, market access, economies of scale, and technology. What emerges from this exercise is a picture that raises concern about future growth in Indian agriculture, and the welfare of the people who depend on agriculture for their livelihood. Agricultural productivity in India appeared to stagnate in the late 1990s after enjoying two decades of rapid growth.

AbstractThe analytic hierarchy process (AHP) is a cornerstone of multi‐criteria decision analysis, enabling well‐informed choices across diverse contexts. This paper introduces an original benchmark‐based framework designed to enhance the precision of consistency classification for pairwise comparison matrices (PCMs) within the AHP methodology. This innovative approach quantifies the discrepancy between a given PCM and its benchmark matrix, comprising comparison ratios that faithfully reflect the relative preferences encapsulated within principal eigenvector values, thereby capturing the true degree of coherence. To ensure benchmark alignment with human perception, elements of the benchmark PCM are further rounded to the nearest values on the Fundamental Scale. The potency of our framework derives from two pivotal factors: the inherent Priority Preference Range within the principal eigenvector and the order of the PCM. Statistical thresholds for consistency are established using a technique based on simulated, logical PCMs, proposed by Bose [2022]. This rigorous method ensures an unbiased, objective and pragmatic evaluation of consistency, eliminating the subjectivity inherent in arbitrary thresholds based on random PCMs. Our approach rectifies the inconsistencies in the conventional CR method that yields false positives for PCMs of orders 3 and 4, and false negatives for higher orders. By harnessing customized benchmarks and eschewing random matrices, our framework systematically confronts the inherent consistency challenges within AHP, thus enhancing its decision‐making capability. The practical utility of our approach is aptly demonstrated through AHPtools, an R‐based library package designed to showcase our novel consistency evaluation method. The demonstration of the package in Appendix B will facilitate readers to easily apply our methodology to real‐world PCM classification scenarios within the AHP. In conclusion, our benchmark‐based framework heralds a transformative era in consistency classification within the AHP, empowering real‐world multi‐criteria decision‐making with unprecedented precision and reliability, and ushering in a new paradigm of informed and astute outcomes.

AbstractA new approach to re‐evaluating consistency in the analytic hierarchy process (AHP) using simulated consistent matrices is presented. The proposed consistency evaluation method makes use of statistically significant deviations from the average consistency measure for the simulated matrices. This addresses most of the deficiencies of the conventional consistency ratio (CR) method. A pairwise comparison matrix (PCM) is adjudged inconsistent by the proposed method if its consistency measure exceeds the modeled consistency threshold. Comparison of the consistency evaluation for simulated nearly‐consistent matrices using the proposed method shows a statistically significant reduction of the order‐specific bias in comparison with the CR method. The proportion of nearly consistent matrices which are evaluated as 'inconsistent' increases more than three‐folds when the evaluation is done using the CR method. Several examples are presented which illustrate the advantages of the proposed method and differences in classification with the CR approach. Evaluation of consistency using the proposed method of statistically derived thresholds from simulated, nearly consistent matrices is more nuanced and objective, as well as intuitive in its interpretability.

"The ten essays in this interdisciplinary collection explore the issues engendered by the popularity of entertainment news, including the role of satire in politics, the declining level of trust in traditional sources of media, the shows' cathartic or informational function, and the ways in which these shows influence public opinion"--Provided by publisher

Cover -- Contents -- List of Figures and Tables -- Acknowledgments -- Introduction -- PART I: Civil War in Sri Lanka and the Birth of the Tamil Diaspora -- CHAPTER ONE: The Rise and Fall of Tamil Militancy in Sri Lanka -- CHAPTER TWO: Tamil Migration to Canada: The Turbulent 1980s and the Birth of a Community -- PART II: The Tamil Diaspora as a Social Movement -- CHAPTER THREE: Taking to the Streets: Diaspora Mobilization, Frame Wars, and the 2009 Protests -- CHAPTER FOUR: New Leadership, New Organizations, and New Hurdles -- CHAPTER FIVE: Tamil Youth and Postwar Movement Identity

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