Evidence map›Paper›PMID 38366098›Full record

ArticleCognitive research: principles and implications2024

Machine translation: Turkish-English bilingual speakers' accuracy detection of evidentiality and preference of MT.

Sümeyra Tosun

Abstract read
In one paragraph

Article in Cognitive research: principles and implications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Sümeyra TosunDepartment of Psychology, Medgar Evers College, CUNY, New York, NY, USA. stosun@mec.cuny.edu.ORCID 0000-0002-5967-1728

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Machine translation (MT) is the automated process of translating text between different languages, encompassing a wide range of language pairs. This study focuses on non-professional bilingual speakers of Turkish and English, aiming to assess their ability to discern accuracy in machine translations and their preferences regarding MT. A particular emphasis is placed on the linguistically subtle yet semantically meaningful concept of evidentiality. In this experimental investigation, 36 Turkish-English bilinguals, comprising both early and late bilinguals, were presented with simple declarative sentences. These sentences varied in their evidential meaning, distinguishing between firsthand and non-firsthand evidence. The participants were then provided with MT of these sentences in both translation directions (Turkish to English and English to Turkish) and asked to identify the accuracy of these translations. Additionally, participants were queried about their preference for MT in four crucial domains: medical, legal, academic, and daily contexts. The findings of this study indicated that late bilinguals exhibited a superior ability to detect translation accuracy, particularly in the case of firsthand evidence translations, compared to their early bilingual counterparts. Concerning the preference for MT, age of acquisition and the accuracy detection of non-firsthand sentence translations emerged as significant predictors.

Indexed as

LanguageMultilingualismTranslationsHumans

Identifiers

PMID38366098
PMCPMC10873250

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.