How many days? A comparison of the quality of time-use data from 2-day and 7-day diaries

Time budget studies differ in the number of diary days. The ‘Guidelines on Harmonized European Time-Use Surveys (HETUS)’ issued by EUROSTAT recommend a two-day diary with both one weekday and one weekend day. In this contribution we examine whether the number of diary days has an effect on the quality of timeuse indicators. A lot of time-use researchers plead for a longer period of observation; some of them even argue that one- or two-day diaries are not very valuable since the high demands of scientific research cannot be accomplished unless multi-day cycles are captured. Longer periods of observation offer better prospects for analyses, especially for the study of rhythms and activity patterns which typically follow cycles of multi-day duration, and which are part of daily life. Other authors however point out that longer periods of observation cause fatigue or diminished motivation and thus will lead to more inaccuracies. In this contribution we use the pooled Flemish time budget data from 1999 and 2004 to compare 7-day diaries with the 2-day diaries as recommended by the EUROSTAT-guidelines. The respondents of the Flemish time use surveys all filled in diaries for 7 consecutive days. To simulate the 2-day registration, we randomly selected one weekday and one weekend day for each respondent. The 2-day selection was compared with the original 7-day registration. The aim of this comparison is to inventory the advantages and disadvantages of the 2-day and 7-day registration method. To do that, we compare different indicators, such as the averages and the standard deviations of the duration of several activities. We further examine whether certain types of activities are more affected by the method of registration than others. Finally we examine whether a longer period of registration negatively affects the quality of the data (less detail and less accurate).Time-budget studies, time-use indicators, methodology

Corpus Annotation for Parser Evaluation

We describe a recently developed corpus annotation scheme for evaluating parsers that avoids shortcomings of current methods. The scheme encodes grammatical relations between heads and dependents, and has been used to mark up a new public-domain corpus of naturally occurring English text. We show how the corpus can be used to evaluate the accuracy of a robust parser, and relate the corpus to extant resources.Comment: 7 pages, LaTeX (uses eaclap.sty

Can Subcategorisation Probabilities Help a Statistical Parser?

Research into the automatic acquisition of lexical information from corpora is starting to produce large-scale computational lexicons containing data on the relative frequencies of subcategorisation alternatives for individual verbal predicates. However, the empirical question of whether this type of frequency information can in practice improve the accuracy of a statistical parser has not yet been answered. In this paper we describe an experiment with a wide-coverage statistical grammar and parser for English and subcategorisation frequencies acquired from ten million words of text which shows that this information can significantly improve parse accuracy.Comment: 9 pages, uses colacl.st