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The broad aim of this paper is to use Noddings' theory of ethical care to analyse mentors' caring experiences. More specifically, it aims to analyse how physical education (PE) mentors provide care, how they are cared for and how this impacts their role within the context of secondary PE initial teacher training (ITT).

Semi-structured interviews were used to generate data from 17 secondary PE mentors within the same university ITT partnership in the north-west of England. Questions focused on the mentors' experiences of care and the impact this had on their wellbeing and professional practice. A process of thematic analysis was used to identify, analyse and report patterns in the data.

The participants reflected established definitions of mentoring by prioritising the aim of developing the associate teachers' (ATs) teaching rather than explicitly providing support for their wellbeing. This aim could be challenging for mentors who face personal and professional difficulties while supporting the training of an AT. Mentors frequently referred to the support of their departmental colleagues in overcoming these difficulties and the importance of developing interdependent caring relationships. Receiving care did not impede mentors from providing support for others; it heightened awareness and increased their desire to develop caring habits.

Teacher wellbeing has drawn greater attention in recent years and is increasingly prioritised in public policy. These findings highlight the value of mentor wellbeing and how caring professional relationships can mitigate the pressures associated with performativity and managing a demanding workload.

The higher-level aim of this study is to investigate the impact of health information needs satisfaction on the fear of COVID-19 for the general population. The investigation is theoretically grounded on Wilsons’ model of information seeking in the context of inquesting the reasons for seeking health information as well as the information sources the general population deploy during the COVID-19 pandemic.

This cross-sectional survey examines the correlations between health information seeking behavior and the COVID-19 generated fear in the general population through the application of a specially designed structured questionnaire which was distributed online. The questionnaire comprised four main distinct research dimensions (i.e. information needs, information sources, obstacles when seeking information and COVID-19 generated fear) that present significant validity levels.

Individuals were motivated to seek COVID-related health information to cope with the pandemic generated uncertainty. Information needs satisfaction as well as digital health literacy levels is associated with the COVID-19 generated fear in the general population. Finally, a conceptual framework based on Wilsons’ macro-model for information seeking behavior was developed to illustrate information needs satisfaction during the pandemic period. These results indicate the need for incentives to enhance health information needs satisfaction appropriately.

The COVID-19 generated fear in the general population is studied through the information seeking behavior lenses. A well-studied theoretical model for information seeking behavior is adopted for health-related information seeking during pandemic. Finally, digital health information literacy levels are also associated with the fear of COVID-19 reported in the authors’ survey.

This article presents two Brazilian Portuguese corpora collected from different media concerning public security issues in a specific location. The primary motivation is supporting analyses, so security authorities can make appropriate decisions about their actions.

The corpora were obtained through web scraping from a newspaper's website and tweets from a Brazilian metropolitan region. Natural language processing was applied considering: text cleaning, lemmatization, summarization, part-of-speech and dependencies parsing, named entities recognition, and topic modeling.

Several results were obtained based on the methodology used, highlighting some: an example of a summarization using an automated process; dependency parsing; the most common topics in each corpus; the forty named entities and the most common slogans were extracted, highlighting those linked to public security.

Some critical tasks were identified for the research perspective, related to the applied methodology: the treatment of noise from obtaining news on their source websites, passing through textual elements quite present in social network posts such as abbreviations, emojis/emoticons, and even writing errors; the treatment of subjectivity, to eliminate noise from irony and sarcasm; the search for authentic news of issues within the target domain. All these tasks aim to improve the process to enable interested authorities to perform accurate analyses.

The corpora dedicated to the public security domain enable several analyses, such as mining public opinion on security actions in a given location; understanding criminals' behaviors reported in the news or even on social networks and drawing their attitudes timeline; detecting movements that may cause damage to public property and people welfare through texts from social networks; extracting the history and repercussions of police actions, crossing news with records on social networks; among many other possibilities.

The work on behalf of the corpora reported in this text represents one of the first initiatives to create textual bases in Portuguese, dedicated to Brazil's specific public security domain.