Self-interests and group-interests in employee involvement programs: A case study

What happens in a unionized setting when a participatory management system is adopted? This question is examined based on a field study of a union manufacturing facility that has been operating under a gainsharing system for four years. As suggested by the political science literature on transforming political systems from authoritarian rule to democracies, the events resemble a complicated chess game among management, union officers, and union members pursuing their self-interests or group-interests during and after the transitional process. Although gainsharing bonuses have been minimal, the democratization of organizational structures and relationships has generated multiple beneficial organizational and individual outcomes for management and union members.     

The Government–Third Sector Interface in Québec

In this paper, the authors analyze different forms of interface between the government and third sector organizations in Québec. In order to do so, they studied relationships in eight different fields of activity: homeless youth services, housing for intellectually deficient people, support organizations for natural caregivers, community leisure centers, community housing for the elderly, daycare centers, social economy organizations for domestic assistance, and services specializing in employment for handicapped people. Following a review of international literature on the relationship between the government and the third sector, the paper analyzes these relationships on the basis of the typology developed by Jennifer M. Coston, which is adapted to the Québécois context. In the eight activity sectors studied, the authors found the presence of four different types of interface between the government and the third sector: “subcontracting,” “coexistence,” “supplementarity,” and “co-construction” relationships.

Confounding adjustment methods for multi-level treatment comparisons under lack of positivity and unknown model specification

Imbalances in covariates between treatment groups are frequent in observational studies and can lead to biased comparisons. Various adjustment methods can be employed to correct these biases in the context of multi-level treatments (> 2). Analytical challenges, such as positivity violations and incorrect model specification due to unknown functional relationships between covariates and treatment or outcome, may affect their ability to yield unbiased results. Such challenges were expected in a comparison of fire-suppression interventions for preventing fire growth. We identified the overlap weights, augmented overlap weights, bias-corrected matching and targeted maximum likelihood as methods with the best potential to address those challenges. A simple variance estimator for the overlap weight estimators that can naturally be combined with machine learning is proposed. In a simulation study, we investigated the performance of these methods as well as those of simpler alternatives. Adjustment methods that included an outcome modeling component performed better than those that focused on the treatment mechanism in our simulations. Additionally, machine learning implementation was observed to efficiently compensate for the unknown model specification for the former methods, but not the latter. Based on these results, we compared the effectiveness of fire-suppression interventions using the augmented overlap weight estimator.     

Reliability analysis of man–machine systems using fuzzy cognitive mapping with genetic tuning

This article offers a method for analyzing the reliability of a man–machine system (MMS) and ranking of influencing factors based on a fuzzy cognitive map (FCM). The ranking of influencing factors is analogous to the ranking of system elements the probabilistic theory of reliability. To approximate the dependence of “influencing factors—reliability,” the relationship of variable increments is used, which ensures the sensitivity of the reliability level to variations in the levels of influencing factors. The novelty of the method lies in the fact that the expert values of the weights of the FCM graph edges (arcs) are adjusted based on the results of observations using a genetic algorithm. The algorithm's chromosomes are generated from the intervals of acceptable values of edge weights, and the selection criterion is the sum of squares of deviations of the reliability simulation results from observations. The method is illustrated by the example of a multifactor analysis of the reliability of the “driver–car–road” system. It is shown that the FCM adjustment reduces the discrepancy between the reliability forecast and observations almost in half. Possible applications of the method can be complex systems with vaguely defined structures whose reliability depends very much on interrelated factors measured expertly.     

Seeing a talking face matters: Infants' segmentation of continuous auditory-visual speech

Visual speech cues from a speaker's talking face aid speech segmentation in adults, but despite the importance of speech segmentation in language acquisition, little is known about the possible influence of visual speech on infants' speech segmentation. Here, to investigate whether there is facilitation of speech segmentation by visual information, two groups of English-learning 7-month-old infants were presented with continuous speech passages, one group with auditory-only (AO) speech and the other with auditory-visual (AV) speech. Additionally, the possible relation between infants' relative attention to the speaker's mouth versus eye regions and their segmentation performance was examined. Both the AO and the AV groups of infants successfully segmented words from the continuous speech stream, but segmentation performance persisted for longer for infants in the AV group. Interestingly, while AV group infants showed no significant relation between the relative amount of time spent fixating the speaker's mouth versus eyes and word segmentation, their attention to the mouth was greater than that of AO group infants, especially early in test trials. The results are discussed in relation to the possible pathways through which visual speech cues aid speech perception.     

Digital platforms and the changing freelance workforce in the Russian Federation: A ten-year perspective

This article traces the development of the online labour market in the Russian Federation and across the wider post-Soviet space. The authors draw on the unique data of four waves of an online survey for 2009, 2011, 2014 and 2019 on the leading Russian-speaking general-purpose platform for creative and knowledge-based work. The results shed light on key trends, such as spatial decentralization, occupational diversification, feminization, maturing, rising educational attainment and educational mismatch, the consolidation of freelance careers, platformization and legalization. The article discusses these findings and their potential policy implications for the future development of online platform work in the Russian Federation.     

Les plateformes de travail numérique et l‘évolution de la main-d‘œuvre en ligne en Fédération de Russie: une analyse sur dix ans

Les auteurs décrivent l'évolution du marché du travail indépendant en ligne en Fédération de Russie et dans l'espace postsoviétique. Les données proviennent d'une enquête originale, adressée à quatre reprises, entre 2009 et 2019, aux utilisateurs d'une grande plateforme d'intermédiation en langue russe, axée sur les métiers créatifs et l'économie du savoir. Plusieurs tendances se dégagent: expansion de l'aire de recrutement; diversification des spécialisations; féminisation, vieillissement et qualification de la main-d'œuvre; péjoration de l'adéquation profil-tâches; consolidation des parcours indépendants en ligne, plateformisation et formalisation. Les auteurs commentent ces évolutions et formulent des recommandations d'action en vue du développement futur du secteur en Fédération de Russie.