Managing projects as a mode of temporal ordering. Performative organising of time and temporality in projects

Purpose Project studies analyse either managing practices or the temporal nature of project management, which leaves open a research gap: the temporality of managing practice. The paper demonstrates that performativity theory with a temporal perspective helps us to understand how managing a project organises limited temporal resources by aligning activities, deadlines or milestones to reach a goal in a given time.Design/methodology/approach The article utilises empirical data and grounded theory methodology. Ten interviews with project managers from two companies support empirically guided theory building and conceptual reasoning.Findings The article extends John Law's “modes of ordering” to a project-specific mode of temporal ordering. This mode of temporal ordering describes the underlying rationale of project managers who assign, order and materialise time to generate the temporal structure of the project.Research limitations/implications The conceptual nature of the paper and its limited empirical data restrict the generalisation of the findings. The article's goal is to initiate further research and to offer a set of tools for such research.Originality/value The contribution links managing practice and temporality in a performativity approach. This link focusses the actual actions of the managers and contextualises them in the temporal flow of the project. Managing projects as a mode of temporal ordering describes how project managers enact temporal structures and how they themselves and their activities are temporally embedded.

Structure, Chronology, and Local Social Meaning of a Supra-Local Vowel Shift: Emergence of the Low-Back-Merger Shift in New England

The Low-Back-Merger Shift (LBMS) is a major North American vowel chain shift spreading across many disparate dialect regions. In this field-based study, we examine the speech of fifty-nine White Western Massachusetts speakers, aged 18–89. Using diagnostics in Becker (2019) and Boberg (2019b), we find the LBMS emerging at the expense of the Northern Cities Shift (Labov, Yaeger, & Steiner, 1972) and traditional New England features (Boberg, 2001; Kurath, 1939; Nagy & Roberts, 2004). In Becker's LBMS model (2019:9), the low-back merger (lot-thought) triggers front-vowel shifts. Our results suggest that local social meaning can sometimes override this chronology such that the front-vowel shifts occur before the low-back merger, even as the overall configuration comes to match Becker's predictions. Sociosymbolic meaning associated with the older New England system has led to a different temporal ordering of LBMS components, thus providing new theoretical and empirical insights into the mechanisms by which supralocal patterns are adopted.

Infrastructuring Leap Seconds : The Regime of Temporal Plurality in Digitally Networked Media

The chapter pursues the hypothesis that the plurality of time in an age of digital interconnectivity imposes itself as a time regime to human and nonhuman entities. By looking at user practices, conventions of time measurement, and temporal operations of digital technologies it is argued that an infrastructural/infrastructuring process consists of the continuous weaving of a relational assemblage between different temporalities, which does not harmonize them, but makes them relevant to each other in their heterogeneity. Thus, the time regime of digitally networked media does not consist of the power constellation of an absolute, “true,” measurable time, but of a fundamental plurality, which becomes visible on the basis of invisible processes and by that challenges all practices of temporal ordering.

Aging and auditory temporal ordering

Background The aging process is characterized by a gradual impairment of several capacities, such as hearing, memory and communication, which implies changes at various levels and, consequently, changes in both hearing and auditory skills, of which the auditory temporal ordering is an example. Methods The sample consisted of 23 elderly individuals, aged between 70 and 96 years (average of 83.09 years) and with mild to severe type I sensorineural hearing loss. For the collection of information, the pure tone audiogram, the frequency and duration pattern tests, the verbal and non-verbal sequential memory tests were used. Results The results revealed that between age and the auditory temporal order tests there was a negative correlation (except in the duration pattern test in the left ear) and between the auditory threshold and the auditory temporal order tests there was negative correlation (except in the duration pattern test in the right ear). Conclusions It is concluded that in this sample the ability of auditory temporal ordering was influenced by aging and hearing loss, which shows that as the age of the elderly progresses and the degree of hearing loss increases the difficulties in temporal auditory processing become larger. This leads us to consider that these elderly have several difficulties in temporal auditory processing and that an intervention as auditory training may be advantageous for the elderly, as it could improve their central auditory processing and, consequently, their hearing, memory and quality of life.

Discourse-Level Event Temporal Ordering with Uncertainty-Guided Graph Completion

Learning to order events at discourse-level is a crucial text understanding task. Despite many efforts for this task, the current state-of-the-art methods rely heavily on manually designed features, which are costly to produce and are often specific to tasks/domains/datasets. In this paper, we propose a new graph perspective on the task, which does not require complex feature engineering but can assimilate global features and learn inter-dependencies effectively. Specifically, in our approach, each document is considered as a temporal graph, in which the nodes and edges represent events and event-event relations respectively. In this sense, the temporal ordering task corresponds to constructing edges for an empty graph. To train our model, we design a graph mask pre-training mechanism, which can learn inter-dependencies of temporal relations by learning to recover a masked edge following graph topology. In the testing stage, we design an certain-first strategy based on model uncertainty, which can decide the prediction orders and reduce the risk of error propagation. The experimental results demonstrate that our approach outperforms previous methods consistently and can meanwhile maintain good global consistency.

Slow Cortical Waves via Cyclicity

Fine-grained information about dynamic structure of cortical networks is crucial in unpacking brain function. Here,we introduced a novel analytical method to characterize the dynamic interaction between distant brain regions,based on cyclicity analysis, and applied it to data from the Human Connectome Project. Resting-state fMRI time series are aperiodic and, hence, lack a base frequency. Cyclicity analysis, which is time-reparametrization invariant, is effective in recovering dynamic temporal ordering of such time series along a circular trajectory without assuming any time scale. Our analysis detected the propagation of slow cortical waves across thebrain with consistent shifts in lead-lag relationships between specific brain regions. We also observed short bursts of strong temporal ordering that dominated overall lead-lag relationships between pairs of regions in the brain, which were modulated by tasks. Our results suggest the possible role played by slow waves of ordered information between brain regions that underlie emergent cognitive function.