Fatima: a digital platform to transform qualitative reasearch in marginalised sectors

定性研究将支持有效的商业活动、非政府组织干预和政府政策，以应对COVID-19的直接影响，更广泛地说，是为了英国更广泛的社会经济复苏。然而，尽管老年人、社会经济弱势群体和融合程度较低的种族人口受到的影响最大，COVID-19进一步增加了这些边缘化且往往是弱势群体的定性研究本已面临的挑战。通过最有效的面对面数据收集-包括访谈、焦点小组和实地工作-由于社交距离和旅行限制，在这些群体中远程开展定性研究面临着可访问性和规模方面的根本障碍，原因是：* 难以获得与大多数连接平台兼容的宽带、计算机和智能手机，数字扫盲率总体较低 * 缺乏技术来管理只能通过固定电话或“非智能”移动的功能手机联系的受访者的数据收集，* 研究设计和敏捷性，以提取复杂而敏感的多维情感数据，考虑到这些受访者的具体情况-这些边缘化和弱势群体中的研究人员的许多目标也可能由于保护或其他原因而削弱了表达直接反应的能力 * 强化分析方法，以清楚地识别和关联这些依赖关系，这些依赖关系跨越更复杂的主题模型和其他隐藏的定性数据变量尽管对可操作的输出的需求增加，但这项工作因此在很大程度上被暂停，现有的定性数据收集数字工具集是以消费者为中心的基于Web/智能手机的应用程序，主要设计用于满足大型企业市场研究人员的需求。这些通常使用自动语音到文本转录，但只支持非常低级别的情感分析，用于简单的严格约束的研究场景。作为回应，Maido正在开发法蒂玛，一个用于定性数据收集和分析的数字平台，它为只能通过功能电话对话访问的边缘化受访者连接了端到端的研究价值链。Maido已经完成了一个成功的证明，概念开发，实现核心数据架构和记录数据收集的远程工作流程。利用他们的最小可行产品和经过验证的转录和自然语言处理工具集，Maido现在寻求将定性功能和编程功能完全开发成一个具有高水平分析自动化的全平台原型。

Qualitative research will underpin effective commercial activities, NGO interventions and government policies to address the direct impacts of COVID-19, and more generally for the UK's wider socio-economic recovery.However, whilst the elderly, socio-economically disadvantaged and less-integrated ethnic demographics are impacted most, COVID-19 has further increased the already unmet challenge of qualitative research within these marginalised and often vulnerable groups.With the most effective face-to-face data gathering - including interviews, focus groups and field work - prevented by social distancing and travel restrictions, remotely undertaking qualitative research within these groups faces fundamental barriers to accessibility and scale due to:* Poor access to broadband, computers and smartphones compatible with most connectivity platforms, and overall low rates of digital literacy* Lack of technology to manage data gathering from respondents who can only be reached via landline or 'non-Smart' mobile feature phones, and integrating effective research workflows across multiple platforms* Study design and agility to extract the complex and sensitive multi-dimensional sentiment data, given these respondents' specific scenarios -- many targets for researchers in these marginalised and vulnerable groups may also have compromised capacity to articulate direct responses for reasons of safeguarding or otherwise* Scalability of costly manually-intensive analysis methodologies to clearly identify and correlate these dependencies across more complex topic models and other hidden qualitative data variablesDespite an increased need for actionable outputs, this work has therefore largely been suspended, both by commercially-active and vertically-integrated research organisations.Existing digital toolsets for qualitative data gathering are consumer-focussed web/smartphone-based applications, which are predominantly designed to meet the needs of large-scale corporate market researchers. These commonly use automated speech-to-text transcription, but support only very low-level sentiment analysis for simple tightly-constrained research scenarios.In response, Maido are developing Fatima, a digital platform for qualitative data collection and analysis, which uniquely connects the end-to-end research value chain for marginalised respondents who can only be accessed via feature phone conversations.Maido have already completed a successful proof-of-concept development, realising the core data architecture and remote workflows for recorded data gathering. Leveraging their minimum-viable-product and proven transcription and natural language processing toolsets, Maido now seek to fully develop the qualitative features and programmatic functionality into a scaled full-platform prototype, with a high level of analytical automation.