Life Cycle and Cohort Productivity in Economic Research: The Case of Germany

Ritzberger, Klaus

doi:10.1111/j.1468-0475.2008.00447.x

Cited by 99 publications

(103 citation statements)

References 52 publications

(82 reference statements)

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“…However, for the 1989 RS E and the 1992 RAE up to two publications from each full-time member of the faculty were RAE and subsequent exercises (Harley and Lee, 1997;Lee and Harley, 1998;and Lee, 2007). It is not difficult to discern why Diamond's list of 27 journals obtained such an elevated status among UK economists: those journals appeared repeatedly as top quality journals in journal ranking studies and in articles that used 'professional judgment' journals to identify the top, blue ribbon, or 'everyone would agree are core, mainstream, highly respected, quality' journals prior to 1989 and since 1989 up to the present day (Lee, 2006;Schneider and Ursprung, 2008;Ritzberger, 2008;Da Silva 2009;Halkos and Nickolaos, 2011;Kalaitzidakis, Mamuneas, and Stengos, 2011); and they appeared to be sanctioned by Economics and Social Research Council, the RES, and CHUDE since they represent ed 16 of the 22 high impact journals identified in their jointly sponsored study, International…”

Section: Journalsmentioning

confidence: 99%

The UK Research Assessment Exercise and the narrowing of UK economics

Lee¹,

Pham²,

Gu³

2013

Cambridge Journal of Economics

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Federated learning (FL) has enabled distributed learning of a model across multiple clients in a privacy-preserving manner. One of the main challenges of FL is to accommodate clients with varying hardware capacities; clients have differing compute and memory requirements. To tackle this challenge, recent state-of-the-art approaches leverage the use of early exits. Nonetheless, these approaches fall short of mitigating the challenges of joint learning multiple exit classifiers, often relying on hand-picked heuristic solutions for knowledge distillation among classifiers and/or utilizing additional layers for weaker classifiers. In this work, instead of utilizing multiple classifiers, we propose a recurrent early exit approach named ReeFL that fuses features from different sub-models into a single shared classifier. Specifically, we use a transformer-based earlyexit module shared among sub-models to i) better exploit multi-layer feature representations for task-specific prediction and ii) modulate the feature representation of the backbone model for subsequent predictions. We additionally present a per-client self-distillation approach where the best sub-model is automatically selected as the teacher of the other sub-models at each client. Our experiments on standard image and speech classification benchmarks across various emerging federated fine-tuning baselines demonstrate ReeFL's effectiveness over previous works.

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Section: Journalsmentioning

confidence: 99%

The UK Research Assessment Exercise and the narrowing of UK economics

Lee¹,

Pham²,

Gu³

2013

Cambridge Journal of Economics

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“…This method called the Invariant method was first introduced by Pinski and Narin (1976) and was adopted by Kodrzycki andYu (2006) andRitzberger (2008). It is notable that Google uses this methodology in order to rank web cites.…”

Section: Until 2004 Wos Was a Monopoly On November 2004 Elsevier Pmentioning

confidence: 99%

“…Ritzberger (2008), argues that most important papers with significant contribution to economic theory are often not cited as this knowledge is considered as given. As a result the most cited papers are not the most important papers.…”

Section: Until 2004 Wos Was a Monopoly On November 2004 Elsevier Pmentioning

confidence: 99%

“…This limitation is confirmed by Garfield (2005) who underlines that 20% of articles receive 80% of citations. Moreover, Ritzberger (2008) presents further limitations which are relative to the peer review system and generally the system of scientific journals.…”

Section: Until 2004 Wos Was a Monopoly On November 2004 Elsevier Pmentioning

confidence: 99%

“…The most significant advantage which is provided by journal rankings is that scientific quality is not hearsay anymore, in fact it is measurable and quantifiable. According to Ritzberger (2008), journal rankings offer relatively objective information about the scientific quality although they suffer from bias and the main reason is their inability to cover all sub-fields of Economics. The two main ranking approaches are peer review and citation analysis (Pujol, 2008).…”

Section: Until 2004 Wos Was a Monopoly On November 2004 Elsevier Pmentioning

confidence: 99%

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Measuring economic journals’ citation efficiency: a data envelopment analysis approach

Halkos

Tzeremes

2011

Scientometrics

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThis paper by using Data Envelopment Analysis (DEA) and statistical inference evaluates the citation performance of 229 economic journals. The paper categorizes the journals into four main categories (A to D) based on their efficiency levels. The results are then compared to the 27 "core economic journals" as introduced by Dimond (1989). The results reveal that after more than twenty years Diamonds' list of "core economic journals" is still valid. Finally, for the first time the paper uses data from four well-known databases (SSCI, Scopus, RePEc, Econlit) and two quality ranking reports (Kiel Institute internals ranking and ABS quality ranking report) in a DEA setting and in order to derive the ranking of 229 economic journals.

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