'They're battle scars, I wear them well': A phenomenological exploration of young women's experiences of building resilience following adversity in adolescence

This is an Author's Accepted Manuscript of an article published in Journal of Youth Studies, 13(3), 273 - 290, 2010 [copyright Taylor & Francis], available online at: http://www.tandfonline.com/10.1080/13676260903520886.This phenomenological study explored young women's accounts of building resilience following chains of adverse life experiences in adolescence. Six participants were interviewed, aged 20–25 years. Most had, or were receiving, a university education. They described their recovery from adversity as starting with certain pivotal moments, followed by both short-term and longer-term strategies. Short-term strategies tended to offer respite from distress and emotional comfort, increased clarity about their experiences and social affirmation. Recovery involved gaining new perspectives on their adverse situation and recovering a positive self-image through three longer-term strategies. These involved making visible progress in their education, rebuilding relationships with family and friends, and participating in the ‘normalizing’ activities and developmental projects of adolescence. Participants believed that they were stronger and more compassionate although positive achievements co-existed with some regrets. Most perceived the adversity as catalyzing personal growth. These accounts of resilience revealed the complex psychosocial processes and resources available to some adolescents

The Parallel Persistent Memory Model

We consider a parallel computational model that consists of $P$ processors, each with a fast local ephemeral memory of limited size, and sharing a large persistent memory. The model allows for each processor to fault with bounded probability, and possibly restart. On faulting all processor state and local ephemeral memory are lost, but the persistent memory remains. This model is motivated by upcoming non-volatile memories that are as fast as existing random access memory, are accessible at the granularity of cache lines, and have the capability of surviving power outages. It is further motivated by the observation that in large parallel systems, failure of processors and their caches is not unusual. Within the model we develop a framework for developing locality efficient parallel algorithms that are resilient to failures. There are several challenges, including the need to recover from failures, the desire to do this in an asynchronous setting (i.e., not blocking other processors when one fails), and the need for synchronization primitives that are robust to failures. We describe approaches to solve these challenges based on breaking computations into what we call capsules, which have certain properties, and developing a work-stealing scheduler that functions properly within the context of failures. The scheduler guarantees a time bound of $O(W/P_A + D(P/P_A) \lceil\log_{1/f} W\rceil)$ in expectation, where $W$ and $D$ are the work and depth of the computation (in the absence of failures), $P_A$ is the average number of processors available during the computation, and $f \le 1/2$ is the probability that a capsule fails. Within the model and using the proposed methods, we develop efficient algorithms for parallel sorting and other primitives.Comment: This paper is the full version of a paper at SPAA 2018 with the same nam