117,396 research outputs found
Wychowanie w Rodzinie / Family Upbringing // Przekaz tradycji i kultury na przestrzeni wieków / The transferring of culture and tradition throughout centuries
No full text<p>Journal:</p>
<p>"Wychowanie w Rodzinie" / "Family Upbringing", Volume I (1/2011). </p>
<p>S. Walasek & L. Albański (Eds.)</p>
<p>Chief Editor: Stefania Walasek</p>
<p>Second Chief Editor: Ewa Jurczyk-Romanowska (since 2013)</p>
<p>Secretary of the Editorial Board: Ewa Jurczyk-Romanowska (till 2013)</p>
<p>Chief Editor: Stefania Walasek<br>Second Chief Editor: Ewa Jurczyk-Romanowska (since 2013)<br>Secretary of the Editorial Board: Ewa Jurczyk-Romanowska (till 2013)<br>ISSN:2082-9019<br>e-ISSN: 2300-5866<br>www.wwr.uni.wroc.pl</p
Health professionals prefer to communicate risk-related numerical information using “1-in-X” ratios.
No full textData sets and code book to accompany Sirota, M., Juanchich, M., Petrova, D., Garcia-Retamero, Walasek, L., Bhatia, S. (2017, March 9). Health professionals prefer to communicate risk-related numerical information using “1-in-X” ratios
Wychowanie w rodzinie. Przekaz tradycji i kultury na przestrzeni wieków, tom 1, red. S. Walasek, L. Albański, Wydawnictwo: Karkonoska Państwowa Szkoła Wyższa w Jeleniej Górze, Jelenia Góra 2011, ss. 276.
No full textWychowanie w rodzinie. Przekaz tradycji i kultury na przestrzeni wieków, tom 1, red. S. Walasek, L. Albański, Wydawnictwo: Karkonoska Państwowa Szkoła Wyższa w Jeleniej Górze, Jelenia Góra 2011, ss. 276
Acceptance of mixed gambles is sensitive to the range of gains and losses experienced, and estimates of lambda (λ) are not a reliable measure of loss aversion : reply to André and De Langhe
No full textWalasek and Stewart (2015) demonstrated that loss aversion estimated from fitting accept–reject choice data from a set of 50–50 gambles can be made to disappear or even reverse by manipulating the range of gains and losses experienced in different conditions. André and de Langhe (2021) critique this conclusion because in estimating loss aversion on different choice sets, Walasek and Stewart (2015) have violated measurement invariance. They show, and we agree, that when loss aversion is estimated on the choices common to all conditions, there is no difference in prospect theory’s λ parameter. But there are two problems here. First, while there are no differences in λs across conditions, there are very large differences in the proportion of the common gambles that are accepted, which André and de Langhe chose not to report. These choice proportion differences are consistent with decision by sampling (but are inconsistent with prospect theory or any of the alternative mechanisms proposed by André & de Langhe, 2021). Second, we demonstrate a much more general problem related to the issue of measurement invariance: that λ estimated from the accept–reject choices is extremely unreliable and does not generalize even across random splits within large, balanced choice sets. It is therefore not possible to determine whether differences in choice proportions are due to loss aversion or to a bias in accepting or rejecting mixed gambles. We conclude that context has large effects on the acceptance of mixed gambles and that it is futile to estimate λ from accept–reject choices
Loss aversion does disappear and reverse, although estimates of lambda (λ) are not reliable: Reply to André and De Langhe
No full textWalasek and Stewart (2015) demonstrated that loss aversion estimated from fitting accept-reject choice data from a set of 50/50 gambles can be made to disappear or even reverse by manipulating the range of gains and losses experienced in different conditions. André and de Langhe (2020) critique this conclusion because in estimating loss aversion on different choice sets, Walasek and Stewart (2015) have violated measurement invariance. They show, and we agree, that when loss aversion is estimated on the choices common to all conditions there is no difference in prospect theory’s λ parameter. But there are two problems here. First, while there are no differences in λs across conditions, there are very large differences in the proportion of the common gambles that are accepted, which André and de Langhe chose not to report. These choice proportion differences are consistent with decision by sampling (but are inconsistent with prospect theory or any of the alternative mechanisms proposed by André and de Langhe, 2020). Second, we demonstrate a much more general issue related to the issue of measurement invariance: that λ estimated from the accept-reject choices is extremely unreliable and does not generalise even across random splits within large, balanced choice sets. It is therefore not possible to determine whether differences in choice proportions are due to loss aversion or to a bias in accepting or rejecting mixed gambles. We conclude that context has large effects on the acceptance of mixed gambles and that it is futile to estimate λ from accept-reject choices
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
Square Dancing with the Stars to Enhance Dynamic Hirschman Linkages?
No full textIn this Presidential Address, the author takes the reader on a reconnaissance of his life and time as a regional scientist. He points out scenery he found scintillating along the way, hoping that some may pick up the banner and chew on a few of the ideas for a while. He suggests a revisit to Albert O. Hirschman’s notion of key sectors and more empirical analysis related to Marcus Berliant’s and Masahisa Fujita’s notion of knowledge creation and transfer.Presidential Address, San Antonio, Texas, March 29, 2014 (53rd Meetings of the Southern Regional Science Association
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Letter from unknown writer to Jesse L. Boyce
No full textLetter to Jesse L. Boyce from unknown author (possibly Jack) about the investigation into the powder magazine located in the Grand Canyon. Some personal news is included in the letter such as the writer's marriage to the daughter of C.A. Taylor, former Supervisor of Cochise County
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
- …
