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EN
chological research, various suggestions have been proposed concerning how to improve the current situation. Among them, a prominent place belongs to replication studies. However the authors aiming to critically evaluate conducted replications or to conduct a replication study themselves needs to explicitly reflect two crucial issues. The first regards conditions that need to be met in order to consider the second study as a replication of the first. This concerns the definition of replication and broader categorization of replication types from a methodological point of view, reflecting various conceptual and terminological issues. The second regards conditions that need to be met in order to say that the results of the replication study replicated/did not replicate the original study. This involves the way in which the study is statistically analysed with respect to its main goal. Therefore, the aim of the present article is to discuss and to summarize the present state of the literature regarding these two issues and to synthesize it into two functional classifications: A, various types of replications from a methodological point of view; B, various possibilities of data analysis from a statistical point of view. It is argued that instead of non-critically preferring one specific approach, the researcher should reflect the pros and cons of various approaches and the broader context of the goal of the replication study.
SK
V rámci prebiehajúcej renesancie psychologického výskumu boli navrhnuté viaceré postupy, majúce potenciál zlepšiť súčasnú situáciu. Medzi nimi zastávajú prominentné postavenie tzv. replikačné štúdie. Autori, ktorý by chceli k realizovaným replikačným štúdiám zaujať kritické stanovisko, alebo replikačnú štúdiu realizovať, potrebujú reflektovať dve dôležité otázky. Prvá sa týka toho, aké podmienky musia byť splnené na to, aby mohla byť štúdia číslo 2 považovaná za replikáciu štúdie číslo 1. To sa úzko dotýka definície toho, čo možno pod replikačnou štúdiou rozumieť, a toho, ako možno replikačné štúdie kategorizovať z metodologického hľadiska, reflektujúc rôzne koncepčné a terminologické otázky. Druhá sa týka toho, aké podmienky je potrebné splniť na to, aby bolo možné tvrdiť, že výsledky replikačnej štúdie predstavujú „úspešnú/ neúspešnú“ replikáciu. To sa úzko dotýka toho, aký štatistický postup analýzy dát je využitý, a toho, aký je hlavný cieľ danej replikačnej snahy. Cieľom tohto príspevku je preto sumarizovať súčasný stav poznania pojednávajúci o týchto dvoch kľúčových aspektoch a následne ho syntetizovať do dvoch funkčných klasifikácií: A) rôznych druhov replikácií z metodologického hľadiska; B) rôznych druhov prístupov k analýze dát zo štatistického hľadiska. Autori argumentujú, že namiesto výlučnej preferencie toho-ktorého prístupu je potrebné reflektovať silné a slabé stránky viacerých prístupov a explicitne zvažovať širší kontext cieľa danej replikácie.
EN
The article discusses Metaphor Identification Procedure Vrije Universiteit (known as MIPVU, Steen et al. 2010) as a method that can be systematically applied to localize metaphorical expressions in discourse. Apart from outlining the steps of the procedure, we focus on the theoretical assumptions underlying its origin as well as point at some benefits and difficulties arising during its application to English and Polish data. The primary aim of the article is to present MIPVU as an attempt at creating a reliable and replicable metaphor identification method that can be used in different text types and different languages.
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EN
The aim of this paper is to initiate the discussion on current trends in sharing research data (and other materials related to the research process) in the Czech linguistic community. First, we present a brief explanation of what the primary incentives are for data sharing. Second, we discuss nine main reasons for sharing data and other research materials. These are verifiability of the results, prophylactic effects, replicability, synergy and cooperation between the researchers, use of data in teaching, social and ethical responsibility, easy accessibility and interpretability of the results, data as an outcome, and the possibility to conduct a meta-analysis. Third, we focus on several examples of good practice, i.e. the Czech National Corpus, the LINDAT/CLARIAH-CZ infrastructure, TROLLing, and the Open Science Framework. As a conclusion of the paper, we present three appeals for Czech linguistics: (a) Academic journals should require data sharing as a standard aspect of the publication process, (b) academic institutions should require sharing of data and other research materials by the academic staff, (c) universities should adopt clear rules for sharing of data and other research materials for students.
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