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Frontmatter -- Preface / Rodney, William -- Contents -- Key to Principal Abbreviations -- Soldiers of the International -- 1. The Roots of Canadian Socialism -- 2. The Years of Uncertainty and Unrest: 1917-1919 -- 3. The Birth of the Canadian Communist Party -- 4. The Rise of the Workers' Party -- 5. Underground Operations and the CPC -- 6. The CPC and the Fourth Comintern Congress -- 7. The CPC and the United Front -- 8. The Emergence of the Canadian Communist Party -- 9. Bolshevization and the Canadian Party -- 10. The Interim Years: 1924-1925 -- 11. The CPC and the Canadian Labor Party -- 12. The CPC and the Trade Union Educational League -- 13. Canadian Party Life: 1925-1926 -- 14. The Seventh Plenum, Comintern Proposals, and Canadian Party Policies -- 15. The Rise of Canadian Trotskyism -- 16. North American Exceptionalism and the Triumph of Stalinism in Canada -- Epilogue -- Appendixes -- Bibliography -- Notes -- Index

AbstractClarivate Analytics, managers of Web of Science, publishes an annual listing of highly cited researchers. The opening sentence of the 2019 report asks "Who would contest that in the race for knowledge, is human capital that is most essential?". They go on to state that "talent—including intelligence, creativity, ambition, and social competence (where needed)—outpaces other capacities such as access to funding and facilities". These contradict previous findings, according to which other factors are possibly more influential than human capital. Using Clarivate Analytics' database for 2018, we investigated which factors are most relevant in development of scientific knowledge. Rather than human capital alone, we found that language, gender, funding, and facilities introduce bias to assessments and possibly prevent talent and discoveries from emerging. We also found that the profile of the highly cited scholars, as established by Clarivate Analytics, is so narrow that it may compromise the validity of scientific knowledge, because it is biased towards the perception and interests of male scholars affiliated with very-highly developed countries where English is commonly spoken and of their sponsors. This highly cited scholars accounted for 76% of the random sample analyzed, absent were women from Latin-America, Africa, Asia, and Oceania, and scholars affiliated with institutions in low-human-developed countries. Also, 98% of the published research came from institutions located in very-highly developed countries. These findings provide evidence that challenges the view that 'talent is the primary driver of scientific advancement'. This is important because search engines, such as Web of Science, can modify their algorithms to ensure the work of scholars that does not fit the currently dominant profile can have their importance increased so that their findings can more equitably contribute to knowledge development. This, in turn, will increase the validity of scientific inquiry.

Purpose
The purpose of this paper is to critically analyze the influence of the algorithm used on scholarly search engines (Garfield's algorithm) and propose metrics to improve it so that science could be based on a more democratic way.


Design/methodology/approach
This paper used a snow-ball approach to collect data that allowed identifying the history and the logic behind the Garfield's algorithm. It follows on excerpting the foundation of existing algorithm and databases of major scholarly search engine. It concluded proposing new metrics so as to surpass restraints and to democratize the scientific discourse.


Findings
This paper finds that the studied algorithm currently biases the scientific discourse toward a narrow perspective, while it should take into consideration several researchers' characteristics. It proposes the substitution of the h-index by the number of times the scholar's most cited work has been cited. Finally, it proposes that works in languages different than English should be included.


Research limitations/implications
The broad comprehension of any phenomena should be based on multiple perspectives; therefore, the inclusion of diverse metrics will extend the scientific discourse.


Practical implications
The improvement of the existing algorithm will increase the chances of contact among different cultures, which stimulate rapid progress on the development of knowledge.


Originality/value
The value of this paper resides in demonstrating that the algorithm used in scholarly search engines biases the development of science. If updated as proposed here, science will be unbiased and bias aware.

Abstract Purpose The purpose of this paper is to critically analyze the influence of the algorithm used on scholarly search engines (Garfield's algorithm) and propose metrics to improve it so that science could be based on a more democratic way. Design/methodology/approach This paper used a snow-ball approach to collect data that allowed identifying the history and the logic behind the Garfield's algorithm. It follows on excerpting the foundation of existing algorithm and databases of major scholarly search engine. It concluded proposing new metrics so as to surpass restraints and to democratize the scientific discourse. Findings This paper finds that the studied algorithm currently biases the scientific discourse toward a narrow perspective, while it should take into consideration several researchers' characteristics. It proposes the substitution of the h-index by the number of times the scholar's most cited work has been cited. Finally, it proposes that works in languages different than English should be included. Research limitations/implications The broad comprehension of any phenomena should be based on multiple perspectives; therefore, the inclusion of diverse metrics will extend the scientific discourse. Practical implications The improvement of the existing algorithm will increase the chances of contact among different cultures, which stimulate rapid progress on the development of knowledge. Originality/value The value of this paper resides in demonstrating that the algorithm used in scholarly search engines biases the development of science. If updated as proposed here, science will be unbiased and bias aware.

Abstract Purpose The purpose of this paper is to critically analyze the influence of the algorithm used on scholarly search engines (Garfield's algorithm) and propose metrics to improve it so that science could be based on a more democratic way. Design/methodology/approach This paper used a snow-ball approach to collect data that allowed identifying the history and the logic behind the Garfield's algorithm. It follows on excerpting the foundation of existing algorithm and databases of major scholarly search engine. It concluded proposing new metrics so as to surpass restraints and to democratize the scientific discourse. Findings This paper finds that the studied algorithm currently biases the scientific discourse toward a narrow perspective, while it should take into consideration several researchers' characteristics. It proposes the substitution of the h-index by the number of times the scholar's most cited work has been cited. Finally, it proposes that works in languages different than English should be included. Research limitations/implications The broad comprehension of any phenomena should be based on multiple perspectives; therefore, the inclusion of diverse metrics will extend the scientific discourse. Practical implications The improvement of the existing algorithm will increase the chances of contact among different cultures, which stimulate rapid progress on the development of knowledge. Originality/value The value of this paper resides in demonstrating that the algorithm used in scholarly search engines biases the development of science. If updated as proposed here, science will be unbiased and bias aware.

The use of financial risk management techniques in the form of
exchange‐rate hedging is widespread in the international business
community, because their use avoids losses owing to volatile
exchange‐rate movements. Identifies the current limited use of such
risk‐hedging techniques in the commercial property market, and considers
potential benefits to international property transactions.