Maturity in reading, revisited: A closer look at adult competent and mature reading

This study investigated the nature of higher-level reading development in adults. Theories of reading development vary in what they identify as the desired endpoints of reading development, with one key difference being whether reading is fundamentally seen as instrumental for accomplishing tasks or as a mode of personal growth. Difficulties associated with understanding higher-level reading development from the point of view of reading as essentially instrumental include the conflict between understandings of higher-level reading development as increasingly specialized and understandings of higher-level reading development as involving consistency of reading performance, even in situations of low knowledge or interest. Gray and Rogers (1956) conducted a study of maturity in reading in which they considered the full flowering of the potential of reading to be the engagement in reading as a form of self-development. This study revisited Gray and Rogers's investigation and expanded upon it by including additional relevant aspects of reading maturity derived from consideration of other theories of reading development and the theoretical and empirical literature on higher-level reading development and by focusing on graduate students as competent and potentially mature readers. The current qualitative, descriptive study aimed at seeing what shape mature and competent reading take with regard to the associated experiences, habits, perceptions, ideas, attitudes, behaviors, and cross-situational reading performance of adult readers with strong academic experience and active regular experience of challenging, specialized reading. Reader profiles were created that highlighted aspects of the data that distinguished possible reading maturity, and three individual and more elaborated exemplary case studies were developed based on those profiles. Finally, descriptions of the underlying phenomena of reading maturity and reading competence were developed. Reading maturity was seen to have the essential character of critical openness, to pursue reading for self-development, and to involve a unified view of reading. Reading competence was seen to have the essential character of being schooled, to pursue reading for task-completion or escape, and to involve the dichotomization of reading into effortful, information-gathering reading of nonfiction for school and pleasurable, entertainment-seeking reading of fiction for personal purposes. In addition, reading competence was seen to take two forms, a generalized cross-situational reading capability, and a situationally-reliant reading that depended on familiarity and interest to support successful reading. This latter form was also connected to the high competence associated with expertise

A simple deterministic near-linear time approximation scheme for transshipment with arbitrary positive edge costs

We describe a simple deterministic near-linear time approximation scheme for uncapacitated minimum cost flow in undirected graphs with real edge weights, a problem also known as transshipment. Specifically, our algorithm takes as input a (connected) undirected graph $G = (V, E)$, vertex demands $b \in \mathbb{R}^V$ such that $\sum_{v \in V} b(v) = 0$, positive edge costs $c \in \mathbb{R}_{>0}^E$, and a parameter $\varepsilon > 0$. In $O(\varepsilon^{-2} m \log^{O(1)} n)$ time, it returns a flow $f$ such that the net flow out of each vertex is equal to the vertex's demand and the cost of the flow is within a $(1 + \varepsilon)$ factor of optimal. Our algorithm is combinatorial and has no running time dependency on the demands or edge costs. With the exception of a recent result presented at STOC 2022 for polynomially bounded edge weights, all almost- and near-linear time approximation schemes for transshipment relied on randomization in two main ways: 1) to embed the problem instance into low-dimensional space and 2) to randomly pick target locations to send flow so nearby opposing demands can be satisfied. Our algorithm instead deterministically approximates the cost of routing decisions that would be made if the input were subject to a random tree embedding. To avoid computing the $\Omega(n^2)$ vertex-vertex distances that an approximation of this kind suggests, we also limit the available routing decisions using distances explicitly stored in the well-known Thorup-Zwick distance oracle