A study on the information seeking behaviour of Singapore-based Filipino domestic workers
Sibal, Hannah Trinity
Date of Issue2015
Wee Kim Wee School of Communication and Information
This research examines the information seeking and use behaviour of Filipino domestic workers (FDWs) in Singapore, who collectively make up around 40% of about 173,000 overseas Filipino workers (OFWs) in this city state. It is based on the premise that low-paid migrants are generally typecast as ‘information poor’, who are left with very common, limiting, and homogeneous information sources. The FDWs are drawn to their co-equals to form an information ground where they can exchange information serendipitously. A survey questionnaire was administered to 138 FDWs to learn about their information behaviour and problems encountered during information seeking. A 5-day ethnographic study in their off-work context supplemented the quantitative data. The study found that FDWs inadequately meet the requisites for digital and information literacy, which are indispensable yet lacking among many low-skilled migrants. Implications about public governance, education, and the pedagogical component of technology use through streamlined information dissemination are discussed to benefit these FDWs.
© 2015 The Authors (Published by SAGE Publications). This is the author created version of a work that has been peer reviewed and accepted for publication in Information Development, published by SAGE Publications on behalf of the authors. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1177/0266666915615929].
Showing items related by title, author, creator and subject.
Snehasish, Banerjee (2017-10-04)This research investigates the ways in which differences between authentic and fictitious reviews on the Internet are related to users’ perceived review authenticity. To accomplish the goal, it addresses two research ...
Hao, Xiao (2014)Multiple kernel learning (MKL) is a family of machine learning techniques by learning with multiple kernel functions/matrices. It has been demonstrated as a promising technique for solving many real-world applications, ...
Sesagiri Raamkumar, Aravind (2018-10-08)In the domain of scholarly communication lifecycle, recommender systems have been built to provide research papers for researchers’ explicit and implicit information needs. Previous studies (Jardine, 2014; Mcnee, 2006) ...