2015JOURNAL OF SOCIAL SCIENCE RESEARCHOpen access

Evaluation of Houses Model of Quality Assessment

Mohsen Askari

Open full text 2 citations

Abstract

There are number of methods, approaches and techniques in evaluating translated texts, but none is as systematic as House (1977, 1997, 2004b, 2007, 2009, 2013, 2015) model of translation quality assessment. The present study was carried out to explore House (1997) model of translation quality assessment (TQA). To pursue this purpose, the model was applied to a psychology textbook. The model is based on functional equivalence and is set to give a thorough analysis of the source language, target language and their comparison. Researchers, however, came to realize some shortcomings in the model; there are basically couple of difficulties with the model. First, House (1997, 2015) does not provide any guide to how much translated text should be assessed i.e. what sample size is needed for the model to operate and be reliable. Another even more serious problem is the fact that one cannot spell out exactly to which degree quality of target text is equal to its source? The researchers proposed two main components to be added to the model, one to the beginning and the other to the end of the model. In order to modify this model in terms of sample size and rating scales, researchers decided to adopt Sical system, which stands for the Canadian Government Translation Bureaus Quality Measurement System in order to have a scale for final quality statement. According to Sical measurement system, a passage of 400 words has been randomly chosen from a psychology textbook and tested against the modified model of quality assessment. Researchers found that the translation could be ranked B fully acceptable. The result shows that the modified model is more systematic and accessible.

Open-access reader

About this research paper

What this paper is about

There are number of methods, approaches and techniques in evaluating translated texts, but none is as systematic as House (1977, 1997, 2004b, 2007, 2009, 2013, 2015) model of translation quality assessment. The present study was carried out to explore House (1997) model of translation quality assessment (TQA). To pursue this purpose, the model was applied to a psychology textbook. The model is based on functional equivalence and is set to give a thorough analysis of the source language, target language and their comparison. Researchers, however, came to realize some shortcomings in the model; there are basically couple of difficulties with the model. First, House (1997, 2015) does not provide any guide to how much translated text should be assessed i.e. what sample size is needed for the model to operate and be reliable. Another even more serious problem is the fact that one cannot spell out exactly to which degree quality of target text is equal to its source? The researchers proposed two main components to be added to the model, one to the beginning and the other to the end of the model. In order to modify this model in terms of sample size and rating scales, researchers decided to adopt Sical system, which stands for the Canadian Government Translation Bureaus Quality Measurement System in order to have a scale for final quality statement. According to Sical measurement system, a passage of 400 words has been randomly chosen from a psychology textbook and tested against the modified model of quality assessment. Researchers found that the translation could be ranked B fully acceptable. The result shows that the modified model is more systematic and accessible.

Why it matters

OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

There are number of methods, approaches and techniques in evaluating translated texts, but none is as systematic as House (1977, 1997, 2004b, 2007, 2009, 2013, 2015) model of translation quality assessment. The present study was carried out to explore House (1997) model of translation quality assessment (TQA). To pursue this purpose, the model was applied to a psychology textbook. The model is based on functional equivalence and is set to give a thorough analysis of the source language, target language and their comparison. Researchers, however, came to realize some shortcomings in the model; there are basically couple of difficulties with the model. First, House (1997, 2015) does not provide any guide to how much translated text should be assessed i.e. what sample size is needed for the model to operate and be reliable. Another even more serious problem is the fact that one cannot spell out exactly to which degree quality of target text is equal to its source? The researchers proposed two main components to be added to the model, one to the beginning and the other to the end of the model. In order to modify this model in terms of sample size and rating scales, researchers decided to adopt Sical system, which stands for the Canadian Government Translation Bureaus Quality Measurement System in order to have a scale for final quality statement. According to Sical measurement system, a passage of 400 words has been randomly chosen from a psychology textbook and tested against the modified model of quality assessment. Researchers found that the translation could be ranked B fully acceptable. The result shows that the modified model is more systematic and accessible.

Key concepts: Quality (philosophy), Statement (logic), Computer science, Sample (material), Equivalence (formal languages), Spell, Scale (ratio), Set (abstract data type)

Related papers

Back to paper searchBrowse research topicsOriginal source
Evaluation of Houses Model of Quality Assessment — Research Paper | ScholarLens