Le travail en équipe dans un univers de production allégée : contrainte ou opportunité

Prenant appui sur des données collectées auprès des travailleurs de l'usine de la GM à Boisbriand, cette étude cherche à mettre en évidence que leur évaluation du travail en équipe est intimement associée à la dynamique sociale qui prévaut au sein des équipes. Les résultats suggèrent que leur évaluation varie selon la capacité de coopération et d'action des travailleurs, laquelle est fortement liée aux modalités du marchandage de l'effort. Dans le cadre de ce marchandage continue sur les lieux de travail, le rôle joué par les chefs d'équipe apparaît comme un enjeu central. Il peut en effet constituer un catalyseur ou un frein à l'émergence de nouvelles capacités d'agir en commun au sein des équipes.A great variety of forms of teamwork exist today, but many questions still remain about their impact. Although the most highly developed forms of teamwork, such as those found at Saturn (Rubinstein, Bennett and Kochan 1993; Shaiken, Lopez and Mankita 1997) and in a number of Volvo plants (Berggren 1992) seem to result in job enrichment, the impact of teamwork in a lean production context appears to be much more uncertain. Research shows that teamwork in the context of lean production does not have a significant impact on the job content of production workers. Even though complementary tasks, such as front-line qualiry control, are integrated into job definitions, there remains a high degree of job fragmentation and standardization (Adler 1993; Babson 1993; Garrahan and Stewart 1992; Graham 1993; Rehder 1994; Robertson et al. 1993). In addition to this process of job standardization and fragmentation, there is also a high degree of work intensification. However, many studies have shown that workers are satisfied with teamwork. Thus, how should workers' satisfaction with teamwork in a context of lean production be understood? Our paper addresses this question.Drawing on a sample of workers (n = 68) from a GM plant in Boisbriand, this paper seeks to demonstrate that pattern of relationship within teams are related to workers' assessment of teamwork. Two main findings emerge from our analysis. First, workers' assessment of teamwork is not straightforward; some workers view teamwork more as a constraint, others assess it more positively, and, between these two extremes are workers whose assessment is fairly neutral. Thus, teamwork cannot be defined uniquely as a constraint or an opportunity. Second, workers' assessment of teamwork is closely linked with the pattern of social relations within their teams, in particular relations between workers and the team leader, which are in turn strongly associated with the nature of effort bargaining.Three patterns of relationships emerge from the data: a mutual exclusion pattern, a mutual adjustment pattern and a cohesive pattern. Workers who define their team relations in terms of mutual exclusion are isolated from each other, in particular from their team leader, and deprived of collective resources. Their inability to cooperate with each other reduces their capacity to exert control over the nature of effort bargaining, which in turn reduces their capacity to alleviate the effects of job intensification. In such a context, teamwork is essentially perceived as a constraint. At the other extreme, there are workers who cooperate with each other and are able to act together (cohesive pattern). These workers are in a position to exercise some form of control over effort bargaining, in particular due to the pivotai role played by the team leader. In these cases, the team leader acts as an intermediary between, on the one hand, the team members, and on the other hand, the foreman and union representatives. The team appears then as a social construct around which a capacity to act collectively is structured. In fact, the team leaders' role as an intermediary seems to increase the teams' capacity for collective action, all of which is linked to the control workers exercise over the effort bargaining and to their positive assessment of teamwork. Between these two extremes are workers who define their team relations in terms of mutual adjustment. Their main resource cornes from their capacity to cooperate with one another and from the team lerders' willingness to act as a buffer by replacing workers on the line. Although this gives them the opportunity to alleviate partly the effects of job intensification, it does not increase their collective influence on decisions. Accordingly, these workers essentially adapt to teamwork without showing much enthousiasm. Although these results are limited by a number of factors, they are nonetheless in line with several studies that show that teamwork in a context of lean production leads to different forms of patterns of relations. In fact, the shift is away from the singularly monolithic vision proposed by Womack, Jones and Roos (1990). These results should not be surprising. As MacDuffie and Pil (1997) have pointed out, the diffusion of the lean production model over the next few years will likely be based on a dual movement: on the one hand, the basic elements of this production model (teamwork, just-intime, continuous improvement, etc.) should become increasingly widespread; but, on the other hand, the implementation of the elements of this model are likely to vary considerably according to regions and firms. However, what is more surprising here is the diversity of views and of patterns of relationships within the same plant and even within the same department. Three hypotheses are suggested to explain this diversity. First, it may be the result of the uncertainty provoked by the decline in the number of workers. It should be pointed out that the data were collected a few months after a massive layoff when demand for the product was continuously falling.Although the effects of the layoff are difficult to measure, it undoubtedly influenced the respondents' answers. Second, it can be hypothesized that this diversity reflects the incomplete nature of ongoing changes. On this view, the plant is in a transition phase and the actors are learning to cope with new production requirements and new roles. Uncertainty, diversity and a blurring of the organizational structure, which are characteristic of transition phases, might thus account for the workers' ambivalence. Third, it can be hypothesized that this diversity is the result of the incomplete nature of the model and its underlying rules. Management principles and rules never apply uniformly in workplaces. There is invariably a gap between prescribed work and real work. Management instructions or collective bargaining agreements do not determine the actors' behaviour and strategies at the shop floor level. Although this hypothesis may seem obvious, it suggests that we need to be cautious in interpreting workplace innovations. In fact, it is one thing to change a rule in the collective agreement and quite another to alter the rule-related practices. Hence, it is important — indeed, vital — to analyze the real nature of workplace changes if we want to understand the nature of innovations in the organisation of work.Basado en los datos recolectados de los trabajadores de la fabrica de GM en Boisbriand, este estudio trata de meter en evidencia que sus evaluaciones del trabajo en equipo estàn directamente asociadas a la dinàmica que prevalece en el seno del equipo. Los resultados sugieren que sus evaluaciones varìan de acuerdo a la capacidad de cooperaciòn y de acciòn de los trabajadores, la cual esta fuertemente ligada a las modalidades de negociaciòn del esfuerzo requerido. En el caso esta negociaciòn continua en los lugares de trabajo, el papel que los lïderes de grupo desempenan, aparece como una parte crucial. Puede en efecto constituir un catalizador o un freno a la emergencia de nuevas capacidades de trabajar en comûn en el seno de los equipos

Tracking and predicting COVID-19 radiological trajectory on chest X-rays using deep learning

Radiological findings on chest X-ray (CXR) have shown to be essential for the proper management of COVID-19 patients as the maximum severity over the course of the disease is closely linked to the outcome. As such, evaluation of future severity from current CXR would be highly desirable. We trained a repurposed deep learning algorithm on the CheXnet open dataset (224,316 chest X-ray images of 65,240 unique patients) to extract features that mapped to radiological labels. We collected CXRs of COVID-19-positive patients from an open-source dataset (COVID-19 image data collection) and from a multi-institutional local ICU dataset. The data was grouped into pairs of sequential CXRs and were categorized into three categories: 'Worse', 'Stable', or 'Improved' on the basis of radiological evolution ascertained from images and reports. Classical machine-learning algorithms were trained on the deep learning extracted features to perform immediate severity evaluation and prediction of future radiological trajectory. Receiver operating characteristic analyses and Mann-Whitney tests were performed. Deep learning predictions between "Worse" and "Improved" outcome categories and for severity stratification were significantly different for three radiological signs and one diagnostic ('Consolidation', 'Lung Lesion', 'Pleural effusion' and 'Pneumonia'; all P < 0.05). Features from the first CXR of each pair could correctly predict the outcome category between 'Worse' and 'Improved' cases with a 0.81 (0.74-0.83 95% CI) AUC in the open-access dataset and with a 0.66 (0.67-0.64 95% CI) AUC in the ICU dataset. Features extracted from the CXR could predict disease severity with a 52.3% accuracy in a 4-way classification. Severity evaluation trained on the COVID-19 image data collection had good out-of-distribution generalization when testing on the local dataset, with 81.6% of intubated ICU patients being classified as critically ill, and the predicted severity was correlated with the clinical outcome with a 0.639 AUC. CXR deep learning features show promise for classifying disease severity and trajectory. Once validated in studies incorporating clinical data and with larger sample sizes, this information may be considered to inform triage decisions

Deep learning of chest X‑rays can predict mechanical ventilation outcome in ICU‑admitted COVID‑19 patients

The COVID-19 pandemic repeatedly overwhelms healthcare systems capacity and forced the development and implementation of triage guidelines in ICU for scarce resources (e.g. mechanical ventilation). These guidelines were often based on known risk factors for COVID-19. It is proposed that image data, specifically bedside computed X-ray (CXR), provide additional predictive information on mortality following mechanical ventilation that can be incorporated in the guidelines. Deep transfer learning was used to extract convolutional features from a systematically collected, multi-institutional dataset of COVID-19 ICU patients. A model predicting outcome of mechanical ventilation (remission or mortality) was trained on the extracted features and compared to a model based on known, aggregated risk factors. The model reached a 0.702 area under the curve (95% CI 0.707-0.694) at predicting mechanical ventilation outcome from pre-intubation CXRs, higher than the risk factor model. Combining imaging data and risk factors increased model performance to 0.743 AUC (95% CI 0.746-0.732). Additionally, a post-hoc analysis showed an increase performance on high-quality than low-quality CXRs, suggesting that using only high-quality images would result in an even stronger model

Experiment, monitoring, and gradient methods used to infer climate change effects on plant communities yield consistent patterns

Inference about future climate change impacts typically relies on one of three approaches: manipulative experiments, historical comparisons (broadly defined to include monitoring the response to ambient climate fluctuations using repeat sampling of plots, dendroecology, and paleoecology techniques), and space-for-time substitutions derived from sampling along environmental gradients. Potential limitations of all three approaches are recognized. Here we address the congruence among these three main approaches by comparing the degree to which tundra plant community composition changes (i) in response to in situ experimental warming, (ii) with interannual variability in summer temperature within sites, and (iii) over spatial gradients in summer temperature. We analyzed changes in plant community composition from repeat sampling (85 plant communities in 28 regions) and experimental warming studies (28 experiments in 14 regions) throughout arctic and alpine North America and Europe. Increases in the relative abundance of species with a warmer thermal niche were observed in response to warmer summer temperatures using all three methods; however, effect sizes were greater over broad-scale spatial gradients relative to either temporal variability in summer temperature within a site or summer temperature increases induced by experimental warming. The effect sizes for change over time within a site and with experimental warming were nearly identical. These results support the view that inferences based on space-for-time substitution overestimate the magnitude of responses to contemporary climate warming, because spatial gradients reflect long-term processes. In contrast, in situ experimental warming and monitoring approaches yield consistent estimates of the magnitude of response of plant communities to climate warming

Greater temperature sensitivity of plant phenology at colder sites: implications for convergence across northern latitudes

Warmer temperatures are accelerating the phenology of organisms around the world. Temperature sensitivity of phenology might be greater in colder, higher latitude sites than in warmer regions, in part because small changes in temperature constitute greater relative changes in thermal balance at colder sites. To test this hypothesis, we examined up to 20 years of phenology data for 47 tundra plant species at 18 high-latitude sites along a climatic gradient. Across all species, the timing of leaf emergence and flowering was more sensitive to a given increase in summer temperature at colder than warmer high-latitude locations. A similar pattern was seen over time for the flowering phenology of a widespread species, Cassiope tetragona. These are among the first results highlighting differential phenological responses of plants across a climatic gradient and suggest the possibility of convergence in flowering times and therefore an increase in gene flow across latitudes as the climate warms

Climate sensitivity of shrub growth across the tundra biome

The tundra biome is experiencing rapid temperature increases that have been linked to a shift in tundra vegetation composition towards greater shrub dominance. Shrub expansion can amplify warming by altering the surface albedo, energy and water balance, and permafrost temperatures. To account for these feedbacks, global climate models must include realistic projections of vegetation dynamics, and in particular tundra shrub expansion, yet the mechanisms driving shrub expansion remain poorly understood. Dendroecological data consisting of multi-decadal time series of annual growth of shrub species provide a previously untapped resource to explore climate-growth relationships across the tundra biome. We analysed a dataset of approximately 42,000 annual growth records from 1821 individuals, comprising 25 species from eight genera, from 37 arctic and alpine sites. Our analyses demonstrate that the sensitivity of shrub growth to climate was (1) heterogeneous across the tundra biome, (2) greater at sites with higher soil moisture and (3) strongest for taller shrub species growing at the northern or upper elevational edge of their range. Across latitudinal gradients in the Arctic, climate sensitivity of growth was greatest at the boundary between low- and high-arctic vegetation zones, where permafrost conditions are changing and the majority of the global permafrost soil carbon pool is stored. Thus, in order to more accurately estimate feedbacks among shrub change, albedo, permafrost thaw, carbon storage and climate, the observed variation in climate-growth relationships of shrub species across the tundra biome will need to be incorporated into earth system models.JRC.H.3-Forest Resources and Climat

Can bryophyte groups increase functional resolution in tundra ecosystems?

Funding Information: This study was supported by a grant to SL from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie, Grant No. 797446 and by the Independent Research Fund Denmark, Grant no. 0135-00140B. Funding from the Academy of Finland (grant 322266), National Science Foundation (1504224, 1836839, PLR-1504381 and PLR-1836898), Independent Research Fund Denmark (9040-00314B), Moscow State University, (project No 121032500089-1), Natural Sciences and Engineering Research Council of Canada, ArcticNet, Polar Continental Shelf Program, Northern Science Training Program, Polar Knowledge Canada, Royal Canadian Mounted Police, Tomsk State University competitiveness improvement program and the Russian Science Foundation (grant No 20-67-46018) are gratefully acknowledged. Matthias Ahrens provided valuable insights on the cushion growth form, and we are most thankful. We thank Gaius Shaver and two anonymous reviewers for providing valuable critique and input to earlier versions of this manuscript. Publisher Copyright: © the author(s) or their institution(s).The relative contribution of bryophytes to plant diversity, primary productivity, and ecosystem functioning increases towards colder climates. Bryophytes respond to environmental changes at the species level, but because bryophyte species are relatively difficult to identify, they are often lumped into one functional group. Consequently, bryophyte function remains poorly resolved. Here, we explore how higher resolution of bryophyte functional diversity can be encouraged and implemented in tundra ecological studies. We briefly review previous bryophyte functional classifications and the roles of bryophytes in tundra ecosystems and their susceptibility to environmental change. Based on shoot morphology and colony organization, we then propose twelve easily distinguishable bryophyte functional groups. To illustrate how bryophyte functional groups can help elucidate variation in bryophyte effects and responses, we compiled existing data on water holding capacity, a key bryophyte trait. Although plant functional groups can mask potentially high interspecific and intraspecific variability, we found better separation of bryophyte functional group means compared with previous grouping systems regarding water holding capacity. This suggests that our bryophyte functional groups truly represent variation in the functional roles of bryophytes in tundra ecosystems. Lastly, we provide recommendations to improve the monitoring of bryophyte community changes in tundra study sites.Peer reviewe