Shifting the Burden: towards more equitable tests for Language Analysis in the Asylum Procedure

转移负担：在庇护程序中进行更公平的语言分析测试

• 批准号: ES/Y007409/1
• 金额: $ 12.65万
• 依托单位: Newcastle University
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FY007409%2F1
• 关键词: Shifting; Burden; towards; more; equitable

Language Analysis in the Asylum Procedure (LAAP) is used by a number of governments, particularly in Europe. Its purpose is to produce a linguistic assessment of claims to origin by asylum applicants who cannot or will not prove their identity by documentary means. LAAP is highly controversial in both academia and the media, yet remarkably little directly relevant experimental work (in)validating its practice has so far been conducted. LAAP depends on applicants' language production (i.e. their speech); in fact, the question in LAAP is, 'To what extent is the applicant's speech identifiable with the area from which they claim to have originated?'. At present, applicants must demonstrate the authenticity of their speech in a one-shot interview, and the assessment of the derived data is carried out by analysts who are native speaker non-linguists (NSNLs) working for LAAP agencies. Yet speech patterns may vary due to past mobility, socio-demographic factors and performance on the day, leaving LAAP assessments open to criticism.This being the case, the core of my research is empirical in nature. It centres not on the speech but on the language perception of applicants-in particular, their ability to identify fellow speakers of their own dialect. Perception is an important aspect of applicants' linguistic competence that has hitherto been overlooked in LAAP. The ultimate objective of my work is the development of novel, robust and evidence-based perception tests that can confirm-or cast doubt on-the primary, speech-based LAAP assessment. These perception tests would complement current LAAP practice by eliciting judgements from applicants themselves, not an NSNL analyst, in identifying authentic samples of their own (claimed) language variety. The PDF will allow me to disseminate to academic audiences the results of experiments piloting these novel tests, and to put the case for their use to LAAP agencies.My experiments mainly concern Syrian Arabic. Quantitative data analysis in my PhD demonstrates significantly superior accuracy for Syrian over non-Syrian NSNLs when identifying utterances in Syrian Arabic. This finding, which is consistent with my initial hypothesis, engenders optimism about a novel perception test involving the same task, since there is no reason to believe that genuine Syrian NSNL asylum applicants would perform significantly worse than the Syrian NSNL listeners in my PhD experiments. This perception test would be founded on the empirically validated performance of the target test groups-(Syrian) Arabic-speaking NSNLs vs. (non-Syrian) Arabic-speaking NSNLs-in my thesis and in further experimental work, conducted during the PDF. The PDF will also allow me to build on analysis of qualitative data in my PhD to develop a second type of perception test. I will examine the cues that listeners cited in identifying their own or other language varieties, and create a series of audio texts in which features are acoustically adjusted or placed in contexts where they do not occur in Syrian Arabic. For example, /e/ could be artificially 'elongated' by the use of computer software, and /q/ placed in words where it does not belong. In the second test, asylum applicants will listen to these texts and be asked to identify the anomalies. My hypothesis is that an authentic Syrian applicant will perceive the extra-long /e/ and the /q/ as not naturally occurring in the speech of a fellow Syrian, while an applicant pretending to be Syrian will lack the linguistic perceptions necessary to recognise the anomalies. Uptake by agencies of these tests would add several layers of validation to extant LAAP practice, thereby enhancing its fairness, rigour and transparency. I will dedicate time within the PDF to engage with LAAP agencies and the media to raise awareness about issues of fairness in LAAP. I will also explore collaborations through which the tests could be adapted for speakers of other dialects and languages.

庇护程序中的语言分析（LAAP）被许多政府使用，特别是在欧洲。其目的是对不能或不愿通过文件手段证明其身份的庇护申请人的原籍申请进行语言评估。LAAP在学术界和媒体中都引起了很大争议，但迄今为止验证其实践的直接相关实验工作却很少。LAAP取决于申请人的语言生产（即他们的讲话）;事实上，LAAP的问题是，“在多大程度上是申请人的讲话与他们声称来自的地区可识别？'.目前，申请人必须在一次性面试中证明其演讲的真实性，并由LAAP机构的母语非语言学家（NSNLs）分析师对所获得的数据进行评估。然而，由于过去的流动性，社会人口因素和当天的表现，言语模式可能会有所不同，这使得LAAP评估受到批评。它的中心不是演讲，而是申请人的语言感知，特别是他们识别自己方言的同伴的能力。感知能力是申请人语言能力的一个重要方面，但在LAAP中一直被忽视。我的工作的最终目标是开发新的，强大的和基于证据的感知测试，可以确认或怀疑的主要，基于语音的LAAP评估。这些感知测试将补充目前的LAAP实践，通过引起申请人自己的判断，而不是NSNL分析师，在确定自己（声称）的语言种类的真实样本。PDF将允许我向学术界传播这些新颖测试的实验结果，并将其应用于LAAP机构，我的实验主要涉及叙利亚阿拉伯语。在我的博士学位定量数据分析表明，显着上级的准确性，为叙利亚在非叙利亚NSNLs时，确定在叙利亚阿拉伯语的话语。这一发现，这是与我最初的假设相一致，产生了一个新的感知测试涉及相同的任务，因为没有理由相信，真正的叙利亚NSNL庇护申请人会比叙利亚NSNL听众在我的博士实验中表现得更差。这种感知测试将建立在经验验证的性能的目标测试组（叙利亚）阿拉伯语NSNLs与（非叙利亚）阿拉伯语NSNLs在我的论文和进一步的实验工作，在PDF期间进行。PDF还将允许我在我的博士论文中建立定性数据分析，以开发第二种类型的感知测试。我将检查听众在识别自己或其他语言变体时引用的线索，并创建一系列音频文本，其中的特征经过声学调整或放置在叙利亚阿拉伯语中不出现的上下文中。例如，/e/可以通过使用计算机软件被人为地“拉长”，而/q/可以被放在不属于它的单词中。在第二个测试中，庇护申请人将听取这些文本，并被要求识别异常情况。我的假设是，一个真正的叙利亚申请人会认为超长的/e/和/q/不是自然发生在一个叙利亚同胞的讲话，而申请人假装是叙利亚将缺乏必要的语言感知识别异常。各机构采用这些测试将为现有的LAAP做法增加几层验证，从而提高其公平性、严格性和透明度。我将在PDF中投入时间与LAAP机构和媒体接触，以提高对LAAP公平问题的认识。我还将探索合作，通过这些测试可以适应其他方言和语言的发言者。