Building TRACE (translations censored) theatre corpus: some methodological questions on text selection

Editores:Micaela Muñoz-Calvo; Carmen Buesa-Gómez

Diez años de investigación sobre teatro traducido en España: el proyecto TRACE y los archivos de censura

[EN] This contribution offers a brief overview of research undertaken for the last few years under the TRACE (translation and censorship, or censored translations) project with respect to theatre. The AGA (General Administration Archive in Alcala de Henares, Madrid), a unique source for information for translation scholars, has become the focus of TRACE-theatre investigations on Francoist Spain in the last few years. In Spain, these censorship archives have proved to be an essential source of information, and a rich reservoir of data that, when explored in depth, help draw a history of Spanish theatre in translation. Contrary to what one may think at first, the purpose of using censorship archives in TRACE is not only to check what got censored (banned, crossed out or modified) but rather to trace back all written evidence left by plays that underwent the bureaucratic censoring process which was applied to all cultural manifestations, national or foreign, theatrical as well as non-dramatic. And it is precisely when tracing back censorship records that one finds a way to uncover a history of Spanish theatre in translation that is yet to be written but can now be outlined.

Translations of industry-based student learning and academic performances

We hypothesized that Industry based learning and teaching, especially through industry assigned student projects or training programs, is an integral part of science, technology, engineering and mathematics (STEM) education. In this paper we show that industry-based student training and experience increases students’ academic performances independent to the organizational parameters and contexts. The literature on industry-based student training focuses on employability and the industry dimension, and neglects in many ways the academic dimension. We observed that the association factors between academic attributes and contributions of industry-based student training are central and vital to the technological learning experiences. We explore international initiatives and statistics collected of student projects in two categories: Industry based learning performances and on campus performances. The data collected were correlated to five (5) universities in different industrialized countries, e.g., Australia N=545, Norway N=279, Germany N=74, France N=107 and Spain N=802 respectively. We analyzed industry-based student training along with company assigned student projects compared with in comparisons to campus performance. The data that suggests a strong correlation between industry-based student training per se and improved performance profiles or increasing motivation shows that industry-based student training increases student academic performance independent of organizational parameters and contexts. The programs we augmented were orthogonal to each other however, the trend of the students’ academic performances are identical. An isolated cohort for the reported countries that opposed our hypothesis warrants further investigation.

Smoothed rank-based procedure for censored data

A smoothed rank-based procedure is developed for the accelerated failure time model to overcome computational issues. The proposed estimator is based on an EM-type procedure coupled with the induced smoothing. "The proposed iterative approach converges provided the initial value is based on a consistent estimator, and the limiting covariance matrix can be obtained from a sandwich-type formula. The consistency and asymptotic normality of the proposed estimator are also established. Extensive simulations show that the new estimator is not only computationally less demanding but also more reliable than the other existing estimators.

Rank regression for accelerated failure time model with clustered and censored data

For clustered survival data, the traditional Gehan-type estimator is asymptotically equivalent to using only the between-cluster ranks, and the within-cluster ranks are ignored. The contribution of this paper is two fold: - (i) incorporating within-cluster ranks in censored data analysis, and; - (ii) applying the induced smoothing of Brown and Wang (2005, Biometrika) for computational convenience. Asymptotic properties of the resulting estimating functions are given. We also carry out numerical studies to assess the performance of the proposed approach and conclude that the proposed approach can lead to much improved estimators when strong clustering effects exist. A dataset from a litter-matched tumorigenesis experiment is used for illustration.

Induced smoothing for rank regression with censored survival times

Adaptions of weighted rank regression to the accelerated failure time model for censored survival data have been successful in yielding asymptotically normal estimates and flexible weighting schemes to increase statistical efficiencies. However, for only one simple weighting scheme, Gehan or Wilcoxon weights, are estimating equations guaranteed to be monotone in parameter components, and even in this case are step functions, requiring the equivalent of linear programming for computation. The lack of smoothness makes standard error or covariance matrix estimation even more difficult. An induced smoothing technique overcame these difficulties in various problems involving monotone but pure jump estimating equations, including conventional rank regression. The present paper applies induced smoothing to the Gehan-Wilcoxon weighted rank regression for the accelerated failure time model, for the more difficult case of survival time data subject to censoring, where the inapplicability of permutation arguments necessitates a new method of estimating null variance of estimating functions. Smooth monotone parameter estimation and rapid, reliable standard error or covariance matrix estimation is obtained.