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Lambert, Peter F, Ra-11815363
No full textThis record was harvested from a previous catalogue system and will be withdrawn in 2025. Information in this record may be superseded or incomplete. Visit this record in UMA's new catalogue at: https://archives.library.unimelb.edu.au/nodes/view/398106Surname: LAMBERT. Given Name(s) or Initials: PETER F. Military Service Number or Last Known Location: RA-11815363. Missing, Wounded and Prisoner of War Enquiry Card Index Number: SEA-3789.237045
Item: [2016.0049.30399] "Lambert, Peter F, Ra-11815363
Scalable wavelet-based coding of irregular meshes with interactive region-of-interest support
No full text
Sequential procedures for poverty gap dominance
No full textPoverty evaluations differ from welfare evaluations in one significant aspect, the existence of a threshold or reference point, the poverty line. We build up normative evaluation models in which comparisons are made taking distances from this reference point rather than from the origin to be ethically relevant, by focussing upon poverty gaps and not incomes. When poverty lines differ for different groups in a socially heterogeneous population, choosing poverty gaps instead of incomes as
the relevant indicator brings in normatively appealing classes of poverty indices not previously accommodated, for which poverty comparisons are implemented through sequential poverty gap curves (or poverty gap distributions) dominance. These conditions
are logically related to those suggested by Atkinson and Bourguignon (Arrow and the foundations of the theory of economic policy, Macmillan, London, 1987) and Bourguignon (J Econom 42:67–80, 1989) for welfare comparisons. However, the proportion of poor individuals in the society and their average poverty gap play a role in our comparisons, though they do not in the existing poverty dominance criteria for heterogeneous populations
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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