Center for Public Policy Studies

Marek Kwiek na Uniwersytecie Kalifornijskim w Berkeley, Spring Speaker Series, Goldman School of Public Policy, 20 kwietnia 2022

Marek Kwiek was invited to have a lecture within Spring Speaker Series, in Goldman School of Public Policy, UC Berkeley, on April 20, 2022.

The link is here: https://cshe.berkeley.edu/big-data-academic-profession-studies-advantages-and-limitations

The lecture organized by the Center for Studies in Higher Education (CSHE) is about:

„Big Data in Academic Profession Studies: Advantages and Limitations”

  The recording of the seminar is available from YouTube: https://youtu.be/XpQFzBaxSQE?t=12

Abstract:

The seminar will be focused on new opportunities for academic profession studies provided by global Big Data and large biographical, administrative, publication and citation datasets. The academic profession research has traditionally used academic surveys. Nowadays, new complementary data sources can be used (raw citation and publication metadata from Scopus and Web of Science, data from merged datasets of different types etc.). New sources radically increase the number of observations, to hundreds of thousands and more – but huge numbers come at a cost, compared with survey instruments. A comparison of advantages and limitations of survey methods (which the author has used extensively for a decade) and large-scale bibliometric methods will be presented. Major topics of the seminar will be the trade-offs in data collection and data analysis; advantages and disadvantages of cloud computing; the power of raw publication and citation metadata; and dataset availability, mergers, and running costs. Academic profession studies face opportunities previously hard to imagine. But some options (for instance, academic attitudes and beliefs) still seem to require large-scale surveys to tackle. Examples of author’s studies on global aging of the academic profession, gender homophily in science, and the global super-class of highly cited researchers will be discussed. The traditional questions of “who they are, how they work” will be translated into Big Data questions applied at the micro-level of individual scientists. Finally, practical implications of the field going global will be explored.

 

Marek Kwiek was invited to have a lecture within Spring Speaker Series, in Goldman School of Public Policy, UC Berkeley, on April 20, 2022.

The link is here: https://cshe.berkeley.edu/big-data-academic-profession-studies-advantages-and-limitations

The lecture organized by the Center for Studies in Higher Education (CSHE) is about:

„Big Data in Academic Profession Studies: Advantages and Limitations”

Abstract:

The seminar will be focused on new opportunities for academic profession studies provided by global Big Data and large biographical, administrative, publication and citation datasets. The academic profession research has traditionally used academic surveys. Nowadays, new complementary data sources can be used (raw citation and publication metadata from Scopus and Web of Science, data from merged datasets of different types etc.). New sources radically increase the number of observations, to hundreds of thousands and more – but huge numbers come at a cost, compared with survey instruments. A comparison of advantages and limitations of survey methods (which the author has used extensively for a decade) and large-scale bibliometric methods will be presented. Major topics of the seminar will be the trade-offs in data collection and data analysis; advantages and disadvantages of cloud computing; the power of raw publication and citation metadata; and dataset availability, mergers, and running costs. Academic profession studies face opportunities previously hard to imagine. But some options (for instance, academic attitudes and beliefs) still seem to require large-scale surveys to tackle. Examples of author’s studies on global aging of the academic profession, gender homophily in science, and the global super-class of highly cited researchers will be discussed. The traditional questions of “who they are, how they work” will be translated into Big Data questions applied at the micro-level of individual scientists. Finally, practical implications of the field going global will be explored.

 

 

Marek Kwiek was invited to have a lecture within Spring Speaker Series, in Goldman School of Public Policy, UC Berkeley, on April 20, 2022.

The link is here: https://cshe.berkeley.edu/big-data-academic-profession-studies-advantages-and-limitations

The lecture organized by the Center for Studies in Higher Education (CSHE) is about:

„Big Data in Academic Profession Studies: Advantages and Limitations”

Abstract:

The seminar will be focused on new opportunities for academic profession studies provided by global Big Data and large biographical, administrative, publication and citation datasets. The academic profession research has traditionally used academic surveys. Nowadays, new complementary data sources can be used (raw citation and publication metadata from Scopus and Web of Science, data from merged datasets of different types etc.). New sources radically increase the number of observations, to hundreds of thousands and more – but huge numbers come at a cost, compared with survey instruments. A comparison of advantages and limitations of survey methods (which the author has used extensively for a decade) and large-scale bibliometric methods will be presented. Major topics of the seminar will be the trade-offs in data collection and data analysis; advantages and disadvantages of cloud computing; the power of raw publication and citation metadata; and dataset availability, mergers, and running costs. Academic profession studies face opportunities previously hard to imagine. But some options (for instance, academic attitudes and beliefs) still seem to require large-scale surveys to tackle. Examples of author’s studies on global aging of the academic profession, gender homophily in science, and the global super-class of highly cited researchers will be discussed. The traditional questions of “who they are, how they work” will be translated into Big Data questions applied at the micro-level of individual scientists. Finally, practical implications of the field going global will be explored.

 

 

 

Marek Kwiek was invited to have a lecture within Spring Speaker Series, in Goldman School of Public Policy, UC Berkeley, on April 20, 2022.

The link is here: https://cshe.berkeley.edu/big-data-academic-profession-studies-advantages-and-limitations

The lecture organized by the Center for Studies in Higher Education (CSHE) is about:

„Big Data in Academic Profession Studies: Advantages and Limitations”

Abstract:

The seminar will be focused on new opportunities for academic profession studies provided by global Big Data and large biographical, administrative, publication and citation datasets. The academic profession research has traditionally used academic surveys. Nowadays, new complementary data sources can be used (raw citation and publication metadata from Scopus and Web of Science, data from merged datasets of different types etc.). New sources radically increase the number of observations, to hundreds of thousands and more – but huge numbers come at a cost, compared with survey instruments. A comparison of advantages and limitations of survey methods (which the author has used extensively for a decade) and large-scale bibliometric methods will be presented. Major topics of the seminar will be the trade-offs in data collection and data analysis; advantages and disadvantages of cloud computing; the power of raw publication and citation metadata; and dataset availability, mergers, and running costs. Academic profession studies face opportunities previously hard to imagine. But some options (for instance, academic attitudes and beliefs) still seem to require large-scale surveys to tackle. Examples of author’s studies on global aging of the academic profession, gender homophily in science, and the global super-class of highly cited researchers will be discussed. The traditional questions of “who they are, how they work” will be translated into Big Data questions applied at the micro-level of individual scientists. Finally, practical implications of the field going global will be explored.

 

Marek Kwiek was invited to have a lecture within Spring Speaker Series, in Goldman School of Public Policy, UC Berkeley, on April 20, 2022.

The link is here: https://cshe.berkeley.edu/big-data-academic-profession-studies-advantages-and-limitations

The lecture organized by the Center for Studies in Higher Education (CSHE) is about:

„Big Data in Academic Profession Studies: Advantages and Limitations”

Abstract:

The seminar will be focused on new opportunities for academic profession studies provided by global Big Data and large biographical, administrative, publication and citation datasets. The academic profession research has traditionally used academic surveys. Nowadays, new complementary data sources can be used (raw citation and publication metadata from Scopus and Web of Science, data from merged datasets of different types etc.). New sources radically increase the number of observations, to hundreds of thousands and more – but huge numbers come at a cost, compared with survey instruments. A comparison of advantages and limitations of survey methods (which the author has used extensively for a decade) and large-scale bibliometric methods will be presented. Major topics of the seminar will be the trade-offs in data collection and data analysis; advantages and disadvantages of cloud computing; the power of raw publication and citation metadata; and dataset availability, mergers, and running costs. Academic profession studies face opportunities previously hard to imagine. But some options (for instance, academic attitudes and beliefs) still seem to require large-scale surveys to tackle. Examples of author’s studies on global aging of the academic profession, gender homophily in science, and the global super-class of highly cited researchers will be discussed. The traditional questions of “who they are, how they work” will be translated into Big Data questions applied at the micro-level of individual scientists. Finally, practical implications of the field going global will be explored.

 

 

 

Marek Kwiek was invited to have a lecture within Spring Speaker Series, in Goldman School of Public Policy, UC Berkeley, on April 20, 2022.

The link is here: https://cshe.berkeley.edu/big-data-academic-profession-studies-advantages-and-limitations

The lecture organized by the Center for Studies in Higher Education (CSHE) is about:

„Big Data in Academic Profession Studies: Advantages and Limitations”

Abstract:

The seminar will be focused on new opportunities for academic profession studies provided by global Big Data and large biographical, administrative, publication and citation datasets. The academic profession research has traditionally used academic surveys. Nowadays, new complementary data sources can be used (raw citation and publication metadata from Scopus and Web of Science, data from merged datasets of different types etc.). New sources radically increase the number of observations, to hundreds of thousands and more – but huge numbers come at a cost, compared with survey instruments. A comparison of advantages and limitations of survey methods (which the author has used extensively for a decade) and large-scale bibliometric methods will be presented. Major topics of the seminar will be the trade-offs in data collection and data analysis; advantages and disadvantages of cloud computing; the power of raw publication and citation metadata; and dataset availability, mergers, and running costs. Academic profession studies face opportunities previously hard to imagine. But some options (for instance, academic attitudes and beliefs) still seem to require large-scale surveys to tackle. Examples of author’s studies on global aging of the academic profession, gender homophily in science, and the global super-class of highly cited researchers will be discussed. The traditional questions of “who they are, how they work” will be translated into Big Data questions applied at the micro-level of individual scientists. Finally, practical implications of the field going global will be explored.

 

 

 

 

Marek Kwiek was invited to have a lecture within Spring Speaker Series, in Goldman School of Public Policy, UC Berkeley, on April 20, 2022.

The link is here: https://cshe.berkeley.edu/big-data-academic-profession-studies-advantages-and-limitations

The lecture organized by the Center for Studies in Higher Education (CSHE) is about:

„Big Data in Academic Profession Studies: Advantages and Limitations”

  The recording of the seminar is available on YouTube: https://youtu.be/XpQFzBaxSQE?t=12

Abstract:

The seminar will be focused on new opportunities for academic profession studies provided by global Big Data and large biographical, administrative, publication and citation datasets. The academic profession research has traditionally used academic surveys. Nowadays, new complementary data sources can be used (raw citation and publication metadata from Scopus and Web of Science, data from merged datasets of different types etc.). New sources radically increase the number of observations, to hundreds of thousands and more – but huge numbers come at a cost, compared with survey instruments. A comparison of advantages and limitations of survey methods (which the author has used extensively for a decade) and large-scale bibliometric methods will be presented. Major topics of the seminar will be the trade-offs in data collection and data analysis; advantages and disadvantages of cloud computing; the power of raw publication and citation metadata; and dataset availability, mergers, and running costs. Academic profession studies face opportunities previously hard to imagine. But some options (for instance, academic attitudes and beliefs) still seem to require large-scale surveys to tackle. Examples of author’s studies on global aging of the academic profession, gender homophily in science, and the global super-class of highly cited researchers will be discussed. The traditional questions of “who they are, how they work” will be translated into Big Data questions applied at the micro-level of individual scientists. Finally, practical implications of the field going global will be explored.

 

Marek Kwiek was invited to have a lecture within Spring Speaker Series, in Goldman School of Public Policy, UC Berkeley, on April 20, 2022.

The link is here: https://cshe.berkeley.edu/big-data-academic-profession-studies-advantages-and-limitations

The lecture organized by the Center for Studies in Higher Education (CSHE) is about:

„Big Data in Academic Profession Studies: Advantages and Limitations”

Abstract:

The seminar will be focused on new opportunities for academic profession studies provided by global Big Data and large biographical, administrative, publication and citation datasets. The academic profession research has traditionally used academic surveys. Nowadays, new complementary data sources can be used (raw citation and publication metadata from Scopus and Web of Science, data from merged datasets of different types etc.). New sources radically increase the number of observations, to hundreds of thousands and more – but huge numbers come at a cost, compared with survey instruments. A comparison of advantages and limitations of survey methods (which the author has used extensively for a decade) and large-scale bibliometric methods will be presented. Major topics of the seminar will be the trade-offs in data collection and data analysis; advantages and disadvantages of cloud computing; the power of raw publication and citation metadata; and dataset availability, mergers, and running costs. Academic profession studies face opportunities previously hard to imagine. But some options (for instance, academic attitudes and beliefs) still seem to require large-scale surveys to tackle. Examples of author’s studies on global aging of the academic profession, gender homophily in science, and the global super-class of highly cited researchers will be discussed. The traditional questions of “who they are, how they work” will be translated into Big Data questions applied at the micro-level of individual scientists. Finally, practical implications of the field going global will be explored.

 

 

Marek Kwiek was invited to have a lecture within Spring Speaker Series, in Goldman School of Public Policy, UC Berkeley, on April 20, 2022.

The link is here: https://cshe.berkeley.edu/big-data-academic-profession-studies-advantages-and-limitations

The lecture organized by the Center for Studies in Higher Education (CSHE) is about:

„Big Data in Academic Profession Studies: Advantages and Limitations”

Abstract:

The seminar will be focused on new opportunities for academic profession studies provided by global Big Data and large biographical, administrative, publication and citation datasets. The academic profession research has traditionally used academic surveys. Nowadays, new complementary data sources can be used (raw citation and publication metadata from Scopus and Web of Science, data from merged datasets of different types etc.). New sources radically increase the number of observations, to hundreds of thousands and more – but huge numbers come at a cost, compared with survey instruments. A comparison of advantages and limitations of survey methods (which the author has used extensively for a decade) and large-scale bibliometric methods will be presented. Major topics of the seminar will be the trade-offs in data collection and data analysis; advantages and disadvantages of cloud computing; the power of raw publication and citation metadata; and dataset availability, mergers, and running costs. Academic profession studies face opportunities previously hard to imagine. But some options (for instance, academic attitudes and beliefs) still seem to require large-scale surveys to tackle. Examples of author’s studies on global aging of the academic profession, gender homophily in science, and the global super-class of highly cited researchers will be discussed. The traditional questions of “who they are, how they work” will be translated into Big Data questions applied at the micro-level of individual scientists. Finally, practical implications of the field going global will be explored.

 

 

 

 

Marek Kwiek was invited to have a lecture within Spring Speaker Series, in Goldman School of Public Policy, UC Berkeley, on April 20, 2022.

The link is here: https://cshe.berkeley.edu/big-data-academic-profession-studies-advantages-and-limitations

The lecture organized by the Center for Studies in Higher Education (CSHE) is about:

„Big Data in Academic Profession Studies: Advantages and Limitations”

Abstract:

The seminar will be focused on new opportunities for academic profession studies provided by global Big Data and large biographical, administrative, publication and citation datasets. The academic profession research has traditionally used academic surveys. Nowadays, new complementary data sources can be used (raw citation and publication metadata from Scopus and Web of Science, data from merged datasets of different types etc.). New sources radically increase the number of observations, to hundreds of thousands and more – but huge numbers come at a cost, compared with survey instruments. A comparison of advantages and limitations of survey methods (which the author has used extensively for a decade) and large-scale bibliometric methods will be presented. Major topics of the seminar will be the trade-offs in data collection and data analysis; advantages and disadvantages of cloud computing; the power of raw publication and citation metadata; and dataset availability, mergers, and running costs. Academic profession studies face opportunities previously hard to imagine. But some options (for instance, academic attitudes and beliefs) still seem to require large-scale surveys to tackle. Examples of author’s studies on global aging of the academic profession, gender homophily in science, and the global super-class of highly cited researchers will be discussed. The traditional questions of “who they are, how they work” will be translated into Big Data questions applied at the micro-level of individual scientists. Finally, practical implications of the field going global will be explored.

 

Marek Kwiek was invited to have a lecture within Spring Speaker Series, in Goldman School of Public Policy, UC Berkeley, on April 20, 2022.

The link is here: https://cshe.berkeley.edu/big-data-academic-profession-studies-advantages-and-limitations

The lecture organized by the Center for Studies in Higher Education (CSHE) is about:

„Big Data in Academic Profession Studies: Advantages and Limitations”

Abstract:

The seminar will be focused on new opportunities for academic profession studies provided by global Big Data and large biographical, administrative, publication and citation datasets. The academic profession research has traditionally used academic surveys. Nowadays, new complementary data sources can be used (raw citation and publication metadata from Scopus and Web of Science, data from merged datasets of different types etc.). New sources radically increase the number of observations, to hundreds of thousands and more – but huge numbers come at a cost, compared with survey instruments. A comparison of advantages and limitations of survey methods (which the author has used extensively for a decade) and large-scale bibliometric methods will be presented. Major topics of the seminar will be the trade-offs in data collection and data analysis; advantages and disadvantages of cloud computing; the power of raw publication and citation metadata; and dataset availability, mergers, and running costs. Academic profession studies face opportunities previously hard to imagine. But some options (for instance, academic attitudes and beliefs) still seem to require large-scale surveys to tackle. Examples of author’s studies on global aging of the academic profession, gender homophily in science, and the global super-class of highly cited researchers will be discussed. The traditional questions of “who they are, how they work” will be translated into Big Data questions applied at the micro-level of individual scientists. Finally, practical implications of the field going global will be explored.

 

 

 

Marek Kwiek was invited to have a lecture within Spring Speaker Series, in Goldman School of Public Policy, UC Berkeley, on April 20, 2022.

The link is here: https://cshe.berkeley.edu/big-data-academic-profession-studies-advantages-and-limitations

The lecture organized by the Center for Studies in Higher Education (CSHE) is about:

„Big Data in Academic Profession Studies: Advantages and Limitations”

Abstract:

The seminar will be focused on new opportunities for academic profession studies provided by global Big Data and large biographical, administrative, publication and citation datasets. The academic profession research has traditionally used academic surveys. Nowadays, new complementary data sources can be used (raw citation and publication metadata from Scopus and Web of Science, data from merged datasets of different types etc.). New sources radically increase the number of observations, to hundreds of thousands and more – but huge numbers come at a cost, compared with survey instruments. A comparison of advantages and limitations of survey methods (which the author has used extensively for a decade) and large-scale bibliometric methods will be presented. Major topics of the seminar will be the trade-offs in data collection and data analysis; advantages and disadvantages of cloud computing; the power of raw publication and citation metadata; and dataset availability, mergers, and running costs. Academic profession studies face opportunities previously hard to imagine. But some options (for instance, academic attitudes and beliefs) still seem to require large-scale surveys to tackle. Examples of author’s studies on global aging of the academic profession, gender homophily in science, and the global super-class of highly cited researchers will be discussed. The traditional questions of “who they are, how they work” will be translated into Big Data questions applied at the micro-level of individual scientists. Finally, practical implications of the field going global will be explored.

 

 

 

 

 

 

 

Marek Kwiek was invited to have a lecture within Spring Speaker Series, in Goldman School of Public Policy, UC Berkeley, on April 20, 2022.

The link is here: https://cshe.berkeley.edu/big-data-academic-profession-studies-advantages-and-limitations

The lecture organized by the Center for Studies in Higher Education (CSHE) is about:

„Big Data in Academic Profession Studies: Advantages and Limitations”

  The recording of the seminar is available on YouTube: https://youtu.be/XpQFzBaxSQE?t=12

Abstract:

The seminar will be focused on new opportunities for academic profession studies provided by global Big Data and large biographical, administrative, publication and citation datasets. The academic profession research has traditionally used academic surveys. Nowadays, new complementary data sources can be used (raw citation and publication metadata from Scopus and Web of Science, data from merged datasets of different types etc.). New sources radically increase the number of observations, to hundreds of thousands and more – but huge numbers come at a cost, compared with survey instruments. A comparison of advantages and limitations of survey methods (which the author has used extensively for a decade) and large-scale bibliometric methods will be presented. Major topics of the seminar will be the trade-offs in data collection and data analysis; advantages and disadvantages of cloud computing; the power of raw publication and citation metadata; and dataset availability, mergers, and running costs. Academic profession studies face opportunities previously hard to imagine. But some options (for instance, academic attitudes and beliefs) still seem to require large-scale surveys to tackle. Examples of author’s studies on global aging of the academic profession, gender homophily in science, and the global super-class of highly cited researchers will be discussed. The traditional questions of “who they are, how they work” will be translated into Big Data questions applied at the micro-level of individual scientists. Finally, practical implications of the field going global will be explored.