Abstract: To facilitate assessment of financial stability and preparedness. In an embodiment, a financial advice system associates a first maximum sub-component value and a first actual value, based on first data related to financial conditions of a first user, with a first sub-component. The financial advice system associates a second maximum sub-component value and a second actual value, based on second data related to the financial conditions of the first user, with a second sub-component. The financial advice system determines a first user score associated with financial stability of the first user based on the first maximum sub-component value and the first actual value associated with the first sub-component and the second maximum sub-component value and the second actual value associated with the second sub-component.

Abstract: A facility for managing an employment opportunity is described. The facility accesses information about an employment opportunity that indicates a maximum number of workers for the employment opportunity. The facility determines that a number of workers equal to the maximum number of workers have claimed the employment opportunity. In response to this determining, the facility causes to be presented to a selected worker an indication that the selected worker may join a waiting list for the employment opportunity. The facility receives input indicating that the selected worker wishes to join the waiting list for the employment opportunity. In response to receiving the input, the facility causes the selected worker to be added to the waiting list for the employment opportunity.

Abstract: Embodiments include methods, systems, and non-transitory computer program products for recommending timely digital content to a user. The method includes receiving a request for a digital content recommendation for a content channel, and selecting a content collection from content collections associated with the content channel, where the content collection contains pre-selected digital content. The method also includes determining digital content candidates from the selected content collection based on pre-determined editorial rankings of digital content candidates or recently popular digital content among users. The method also includes filtering the digital content candidates to determine at least one recommended digital content candidate, where the filtering is based on a length of a digital content candidate, a date and time associated with the digital content candidate, or whether the user has previously consumed the digital content candidate.