The Alternation Of Shi,Ling And Rang In Chinese Analytic Causative Constructions

This study examines the onomasiological choice of three near-synonymous Chinese causative markers,i.e.shi,rang and ling and its lectal variation in Mainland Chinese(MC),Taiwan Chinese(TC)and Singapore Chinese(SC)using the ‘Tagged Chinese Gigaword Corpus’.All the observations with shi,rang and ling were automatically retrieved from a sub-corpus(around six million words)and then were manually checked to avoid spurious hits.We randomly selected 3070 observations(30% of all valid observations)and annotated them with 27 predictors.Then,we used conditional inference trees and random forests to disentangle the interactions between predictors and to obtain an importance ranking of all the predictors.Finally,a multinomial logistic regression model was built with the significant predictors evaluated by the random forest.Our analyses show that: 1)the CAUSEE of ling-constructions tends to be an experiencer with the form of ren,followed by adjectives,and ling-constructions significantly appear more in a relative clause,showing a lexicalization tendancy;2)both shi and rang are more favored when the effected predicate is a transitive verb or a copula;3)the probability of rang significantly increases when CAUSEE is an agent,whereas shi is more favored when CAUSEE is a theme or a patient;4)VARIETY is evaluated by the random forest to be the most imporant predictor.The multinomial logistic regression further detects significant interaction between VARIETY and CLAUSETYPE: The influence of CLAUSETYPE is stronger in MC,with shi and rang favoring different clause types,whereas in TC and SC rang is always more favored than shi.The three varieties do not show significant variation on the usage of ling.To conclude,the choice of shi,ling and rang is jointly affected by multiple factors,and significant lectal variation has been found.This study not only shows the benefit of Cognitive Sociolinguistics for synthetically analyzing language internal and external factors,but also contributes to the research on Chinese analytic causative constructions and variation in Chinese varieties by analyzing large-scale data and incorporating considerable predictors.