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ALLSTAT  October 2010

ALLSTAT October 2010

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Subject:

Reminder: this wed, RSS Lancashire/Cumbria local group, OCT 20 (Wed), 3pm

From:

Ting-Li Su <[log in to unmask]>

Reply-To:

Ting-Li Su <[log in to unmask]>

Date:

Mon, 18 Oct 2010 15:29:29 +0100

Content-Type:

text/plain

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Just a reminder of an interesting talk coming this Wednesday!  Tea/Biscuit
will be served at 4pm. 


Title: Bibliometrics and the REF & REF equalities analysis


Speaker: Mark Gittoes, Analytical Services Group, HEFCE

Venue: PSC Lecture Theatre , Lancaster University

Time: 2010-10-20 15:00 (Wed)

Please note the new time/venue for the talk.

All welcome!

Ting-Li Su

Secretary,

RSS Lancashire/Cumbria Local Group

############################################

ABSTRACT

HEFCE are currently developing a new system for examining the quality of
research in UK HEIs. The primary focus of the system will be to identify
excellent research of all kinds and this will be assessed through a process
of expert review, potentially informed by citation information in subjects
where robust data are available. This talk reports on two technical aspects
of citation information which will help inform HEFCE's consultations on the
process. 

An important part of any approach to bibliometrics is benchmarking. The
citation count of a piece of work, by itself, tells us little about it;
citations accumulate with time, and rates of citation vary substantially
between academic disciplines. In the first aspect discussed, we will look at
the approaches to benchmarking (or normalising) citation counts against
cohorts of similar outputs. Conventionally an output is benchmarked against
the mean citation score of its cohort. We will discuss an alternative
approach using percentiles. 

In the second aspect, we will discuss an equalities analysis that was
carried out using citation information. This considered the question of
whether early career researchers (ECRs) were more or less likely than
non-ECRs to be 'highly cited' on two citation databases. The analysis also
considered other equality areas such as sex, ethnicity & disability and used
statistical models to compare staff on a like for like basis.

 


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