Results and discussion
7.1 Statistical Methods
The statistical analysis were made with SAS v9.2 statistical software. A p-value of<0.05 was set as the level of significance used to justify that a claim can be considered as statistically significant.
7.1.1 Descriptive summary
For each of the indicators frequency table with absolute and relative frequencies were represented using bar graphs. For each of the four categories and for the total number of indicators have been calculated summary statistics: mean, median, minimum and maximum were represented using bar graphs.
7.2 Results
7.2.1 General results
Figure 7.1: Overall explicitation traces per translation editing environ-ment
Figure 7.2: Overall explicitation traces per translator profile
Figure 7.3: Overall explicitation traces per text
7.2.2 Bivariate analysis
Bivariate analysis is the simultaneous analysis of two variables or attributes. It explores the relationship between two variables in order to identify whether there exists an association and the strength of this association, or whether there are differences between two variables and the significance of these differences. In the bivariate analyses each of the explicitation indicators has been compared with each of the following variables: i) translation editing environment, ii) text, iii) position of the translation editing environment used to translate, iv) gender of the translator, v) translator profile and vi) translation shift in the experiment.
Stacked Column charts were used to visualize the relationship between two categorical variables (presence or absence of the explicitation indicator), comparing the percentage that each category from one variable contributes to a total across categories of the second variable. The analyses were performed using logistic regression models considering repeated measurements of individuals.
For the sum of indicators of each category and the total number of indicators sum-mary statistics have been calculated and plotted graphically using box diagrams. The analyses were performed using generalized linear regression models considering repeated measurements of individuals.
For the analysis of translation time linear mixed models with repeated measures were considered for the following the explanatory variables: i) translation editing environment, ii) text, iii) position of the translation editing environment used to translate, iv) gender of the translator, v) translator profile and vi) translation shift in the experiment. Time has also been plotted using box diagrams.
User satisfaction and ratings of perceived difficulty as collected in the post-translation questionnaire were process using non-parametric test (Mann-Whitney-Wilcoxon and Kruskal-Wallis) for the following the explanatory variables: : i) translation editing envir-onment, ii) text, iii) position of the translation editing environment used to translate, iv)
gender of the translator, v) translator profile and vi) translation shift in the experiment.
Time has also been plotted using box diagrams.
7.2.2.1 Summary and discussion (Hypothesis H1)
7.2.3 Implicit to explicit cultural and contextual refer-ences
Figure 7.4: Implicit to explicit cultural/contextual referents per envir-onment
p-value<0.64 (not statistically significant)
Figure 7.5: Implicit to explicit cultural/contextual referents per trans-lator profile
p-value<0.23 (not statistically significant)
Figure 7.6: Implicit to explicit cultural/contextual referents per text p-value<0.48 (not statistically significant)
7.2.4 Phoric to fully lexical phrases
Figure 7.7: Phoric to fully lexical phrases per environment p-value<0.20 (not statistically significant)
Figure 7.8: Phoric to fully lexical phrases per translator profile p-value<0.078 (not statistically significant)
Figure 7.9: Phoric to fully lexical phrases per text p-value <0.0001 (highly statistically significant)
7.2.5 Newly introduced cohesive referents per discourse segment
Figure 7.10: Newly introduced cohesive referents per environment p-value <0.0034 (statistically significant)
Figure 7.11: Newly introduced cohesive referents per translator profile p-value <0.0496 (statistically significant)
Figure 7.12: Newly introduced cohesive referents per text p-value <0.0002 (highly statistically significant)
7.2.6 Lexical specification
Figure 7.13: Lexical specification traces per environment p-value<0.1555 (not statistically significant)
Figure 7.14: Lexical specification traces per translator profile p-value <0.0013 (statistically significant)
Figure 7.15: Lexical specification traces per text p-value <0.0001 (highly statistically significant)
7.2.7 Time and translation editing environment
Figure 7.16: Overall time to complete the task per translation editing environment
p-value<0.9728 (not statistically significant)
Figure 7.17: Overall time to complete the task per text p-value<0.8879 (not statistically significant)
Figure 7.18: Overall time to complete the task per text/environment position
p-value<0.0001 (not statistically significant)
Figure 7.19: Overall time to complete the task per translator profile p-value<0.7028 (not statistically significant)
The following interactions in the bivariant analyses did not turn to be statically significant:
time and gender: p-value<0.3476.
user satisfaction and environment used to translate: p-value<0.7518.
user satisfaction and position of the text/environment: p-value<0.6684.
user satisfaction and translator gender: p-value<0.1141.
user satisfaction and translator profile: p-value<0.7818.
user satisfaction and translation shift in the experiment: p-value<0.1989.
text difficulty and environment used to translate: p-vale<0.6622.
text difficulty and position of the text/environment: p-value<0.0954.
text difficulty and translator gender: p-value<0.8181.
text difficulty and translator profile: p-value<0.1348.
text difficulty and translation shift in the experiment: p-value<0.0681.
7.2.8 User satisfaction evaluation
For the interaction between user satisfaction and translated text there is a a significant different among texts (p-value<0.0497):
Figure 7.20: Satisfaction rate per text
7.2.9 Text difficulty evaluation
For the interaction between text difficulty as perceived by the translator and the three text there are significant differences being text 2 the most difficult to translate according to the feedback provided by the translator in the post-translation questionnaire:
Figure 7.21: Text difficulty per translated text
7.2.10 Multivariate analysis
Multivariate statistical analysis refers to multiple advanced techniques for examining relationships among multiple variables at the same time. This type of analysis is desirable because researchers often hypothesize that a given outcome of interest is effected or influenced by more than one thing. Multiple regression analysis, often referred to simply as regression analysis, examines the effects of multiple independent variables (predictors) on the value of a dependent variable, or outcome. We analyzed the different indicators using generalized linear regression models with repeated measures considering the environment as explanatory variables for the following the explanatory variables: i) translation editing environment, ii) text, iii) position of the translation editing environment used to translate, iv) gender of the translator, v) translator profile and vi) translation shift in the experiment, vii) translation time, viii) satisfaction and ix) perceived text difficulty.
We have also considered interaction between translation editing environment and text position in the translation task. For each category of the explanatory variables were calculated odds ratios (OR) or relative risk (RR) with respect to the other categories at a confidence interval of 95
7.2.11 Implicit to explicit cultural and contextual ref-erences
In terms of implicit to explicit cultural and contextual references, the multivariate analysies did not found statistically significant differences for the variables under analyses.
7.2.12 Phoric to fully lexical phrases
The multivariant analyses performed for this category turned to show significant differences depending on the environment and the text used to translate.
OR Standard Error Confidence Limits Chi-Square Pr>ChiSq
E1 22.268 0.7424 11.585 42.803 5.77 0.0163
E2 0.6636 0.1971 0.3708 11.877 1.91 0.1674
E3 0.6767 0.2093 0.3691 12.406 1.59 0.2067
T1 0.0456 0.0210 0.0185 0.1124 44.97 <.0001
T2 17.583 0.5767 0.9245 33.441 2.96 0.0853
T3 124.844 41.031 65.556 23.775 59.00 <.0001
Table 7.1: Environment vs text interaction for phoric to fully lexical phrases category
Translators as a whole introduced made more phoric to fully lexical replacements in E1 as compared with E2 and E3. When examining the interaction between environment and texts, T3 was the one with more phoric to fully lexical replacements and T1 recorded less.
7.2.13 Newly introduced cohesive referents per discourse segment
The interaction for newly introduced cohesive referents per discourse segment showed a significant difference when comparing translation environment, text and translator profile as shown in table 7.2
RR Standard Error Confidence Limits Chi-Square Pr>ChiSq
E1 17.080 0.1255 13.356 21.841 18.20 <.0001
E2 0.7085 0.1570 0.5208 0.9637 4.82 0.0281
E3 0.8264 0.1366 0.6323 10.801 1.95 0.1628
T1 0.7169 0.1471 0.5373 0.9566 5.12 0.0237
T2 0.8260 0.1557 0.6087 11.209 1.51 0.2198
T3 16.886 0.1175 13.414 21.258 19.89 <.0001
Freelancer 13.461 0.1455 10.121 17.903 4.17 0.0411
In-House 11.177 0.1776 0.7891 15.832 0.39 0.5309
Novice 0.6646 0.1819 0.4653 0.9493 5.04 0.0247
Table 7.2: Environment/Text/Profile interaction for Newly introduced cohesive referents per discourse segment category
Translators produce more newly cohesive reference for E1 and E2.
Translators have introduced more cohesive devices in T3 and less in T1.
Freelancer translators have introduced more cohesive devices while novice translators have introduced less.
For the interaction between translation environment and text, E2 and E3 have lesss cohesive devices for T3 than for T1 and T2.
Entorn Text Text Estimate Lower Confidence Limit Upper Confidence Limit ChiSquare Pr>Chi
E1 T1 T2 12.775 0.7696 21.207 0.90 0.3435
E1 T1 T3 11.057 0.7196 16.989 0.21 0.6465
E1 T2 T3 0.8655 0.5685 13.177 0.45 0.5006
E2 T1 T2 0.9478 0.4631 19.394 0.02 0.8832
E2 T1 T3 0.5318 0.2905 0.9735 4.19 0.0407
E2 T2 T3 0.5611 0.3279 0.9599 4.45 0.0349
E3 T1 T2 10.965 0.4836 24.866 0.05 0.8254
E3 T1 T3 0.4070 0.2315 0.7155 9.75 0.0018
E3 T2 T3 0.3711 0.1925 0.7158 8.75 0.0031
Table 7.3: Environment/Text interaction for Newly introduced cohesive referents per discourse segment category
7.2.14 Lexical specification
The total number of cases of lexical specifications show significant differences depending on the text and the translator profile.
Text 2 recorded more explicitation traces of this kind while T1 received less.
Novice translators have introduced less traces for this category while in-house translators have introduced more.
RR Standard Error Confidence Limits Chi-Square Pr>ChiSq
T1 0.4754 0.1237 0.3731 0.6058 36.14 <.0001
T2 18.024 0.0822 15.341 21.176 51.32 <.0001
T3 11.670 0.0959 0.9670 14.083 2.59 0.1073
Freelancer 10.548 0.1134 0.8446 13.173 0.22 0.6380
In-House 16.179 0.1054 13.158 19.893 20.82 <.0001
Novice 0.5860 0.1649 0.4241 0.8096 10.50 0.0012
Table 7.4: Text/Profile interaction for Lexical specification category