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Extreme weather events and failure to adapt to the likely impacts of climate change are two of the most significant threats to humanity. Therefore, many local communities are preparing adaptation plans. Even so, much of what was done has not been published in the peer-reviewed literature. This means that consideration of adaptation options for local communities is limited. With the objective of assisting in the development of adaptation plans, we present 80 adaptation options suitable for coastal communities that can be applied by local governments. They are a catena of options from defend to co-exist and finally, retreat that progresses as impacts become less manageable. Options are organized according to their capacity to protect local properties and infrastructure, natural systems, food production, availability of fresh and drinking water and well-being of the local population, as these are likely to be affected by climate change. To respond to multiple threats, &lsquo ; soft&rsquo ; options, such as awareness raising, planning, political articulation and financial incentives, insurance and professional skills enhancement, can be encouraged immediately at relatively low cost and are reversible. For specific threats, options emphasize change in management practices as pre-emptive measures. Key audiences for this work are communities and local governments starting to consider priority actions to respond to climate change impacts.

Extreme weather events and failure to adapt to the likely impacts of climate change are two of the most significant threats to humanity. Therefore, many local communities are preparing adaptation plans. While so, much of what was done has not been published in the peer-reviewed literature. This means that consideration of adaptation options for local communities is limited. With the objective of assisting on the development of adaptation plans, here we present 80 adaptation options as suitable for coastal communities and can be applied by local governments. They are a catena of options from defend to co-exist and finally retreat that progresses as impacts become less manageable. Options are organized according to their capacity to protect local properties and infrastructure, natural systems, food production, availability of fresh and drinking water and well-being of the local population, as these are likely to be affected by climate change. To respond to multiple threats, 'soft' options of awareness raising, planning, political articulation and financial incentives, insurance and professional skills enhancement can be encouraged immediately at relatively low cost and are reversible. For specific threats, options emphasize change in management practices as pre-emptive measures. Key audiences for this work are communities and local governments starting to consider priority actions to respond to climate change impacts.

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.

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 residesin demonstrating that the algorithm usedin scholarly search engines biases the development of science. If updated as proposed here, science will be unbiased and bias aware.

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 residesin demonstrating that the algorithm usedin scholarly search engines biases the development of science. If updated as proposed here, science will be unbiased and bias aware.

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 For decades, conservation initiatives considered the protection of nature and human progress to be mutually exclusive. As a result of this paradigm, communities living within protected areas often were displaced or treated as invaders and criminals in their ancestral territories. Consequently, much cultural heritage, including traditional knowledge, has been lost. In part to prevent cultural loss, in the year 2000, Brazil legally acknowledged within Federal Act 9,985 the rights, knowledge and way of living of traditional people as integral for the conservation of nature. Based on the case of the traditional Caiçara community living at Martin de Sá (Rio de Janeiro, Brazil), this study showcases fifteen years of cultural change influenced, among others, by the implementation of protected area policy and growth in tourism. Participatory observation between 2000 and 2015 identified changes to the community's way of thinking, lifestyle and livelihoods. Strategies are proposed to increase cultural protection.