TY - CONF
T1 - Identifying Patterns of Participant Shifts in the Psalms
AU - Erwich, C.M.
PY - 2017/10
Y1 - 2017/10
N2 - A great challenge of reading the Hebrew poetry of the Psalms is the identification of participants. The major cause of this problem is a continual shift in person, gender and number (so-called PGN-shifts, or participant shifts) in the text. To account for these PGN-shifts, scholars have always used a more intuitive literary analysis. Instead of studying the problem of PGN-shifts first however, this exegetical tradition offered diffuse explanations of: 1. Who the speakers are in the Psalms: a psalmist, priest, king, prophet or God?; and 2. What the setting and genre is of these texts: e.g., liturgy, oracle or doxology? The current scholarly approaches therefore lack a systematic registration and identification of patterns of PGN-shifts in the Psalms, as well as a methodologically adequate analysis to substantiate claims about speaker or genre.To make a start with a more systematic analysis of PGN-shifts, the Text-Fabric framework is used for a computer-assisted interpretation. Text-Fabric, a Python 3.x software package, operates on the Eep Talstra Center for Bible and Computer (ETCBC) database of the Hebrew Bible plus its (linguistic) annotations. Since the database makes large-scale computation possible a linguistic five-step analysis of PGN-shifts of the whole Hebrew Bible is made in order to methodologically identify patterns of PGN-shifts in the Psalms. Firstly: the data on person, number, and gender of all verbs, pronomina and suffixes are collected from the ETCBC-database. Secondly, from the PGN collection chunks of strings of PGN-shifts are generated. Thirdly, after chunking, the similarities between pairs of chunks are computed. Fourthly, on the basis of a similarity matrix, all similar chunks are organized in groups. As a final step, groups of similar PGN-shift patterns are evaluated in light of the question if they can be meaningful for the formulation of new ideas on speaker and genre in the Psalms.
AB - A great challenge of reading the Hebrew poetry of the Psalms is the identification of participants. The major cause of this problem is a continual shift in person, gender and number (so-called PGN-shifts, or participant shifts) in the text. To account for these PGN-shifts, scholars have always used a more intuitive literary analysis. Instead of studying the problem of PGN-shifts first however, this exegetical tradition offered diffuse explanations of: 1. Who the speakers are in the Psalms: a psalmist, priest, king, prophet or God?; and 2. What the setting and genre is of these texts: e.g., liturgy, oracle or doxology? The current scholarly approaches therefore lack a systematic registration and identification of patterns of PGN-shifts in the Psalms, as well as a methodologically adequate analysis to substantiate claims about speaker or genre.To make a start with a more systematic analysis of PGN-shifts, the Text-Fabric framework is used for a computer-assisted interpretation. Text-Fabric, a Python 3.x software package, operates on the Eep Talstra Center for Bible and Computer (ETCBC) database of the Hebrew Bible plus its (linguistic) annotations. Since the database makes large-scale computation possible a linguistic five-step analysis of PGN-shifts of the whole Hebrew Bible is made in order to methodologically identify patterns of PGN-shifts in the Psalms. Firstly: the data on person, number, and gender of all verbs, pronomina and suffixes are collected from the ETCBC-database. Secondly, from the PGN collection chunks of strings of PGN-shifts are generated. Thirdly, after chunking, the similarities between pairs of chunks are computed. Fourthly, on the basis of a similarity matrix, all similar chunks are organized in groups. As a final step, groups of similar PGN-shift patterns are evaluated in light of the question if they can be meaningful for the formulation of new ideas on speaker and genre in the Psalms.
M3 - Paper
T2 - Plotting Poetry: On Mechanically Enhanced Reading
Y2 - 5 October 2017 through 7 October 2017
ER -