Le débat sur la diglossie en France : aspects scientifiques et politiques

This article outlines the diglossic approach to intra-speaker grammatical variation (Ferguson 1959), wherein speaker—hearers acquire two grammars which are socio-stylistically distinct – one H(igh), the other L(ow) – but linguistically related (to the extent that users regard them as the same language), and then engage one or other of them (but do not mix them) in their active productions. It then sets out how a case could be made for such a model to capture variation in contemporary France, in place of the variationist model which envisages a single, flexible grammar, e.g., the bipolarity, strength and non-random nature of the sociolinguistic H—L distinction, the differing pattern of acquisition of H and L forms, the tendency for L forms to encroach on H terrain (rather than vice versa), and the internal coherence of each of the H and L varieties. Finally, the article sketches the politico-moral dimension to the debate, extending beyond scientific objectivity, and relating to the treatment of non-standard linguistic behaviour in context of the socio-cultural status of the standard

Influence of blood glucose on heart rate and cardiac autonomic function. The DESIR study.

International audienceOBJECTIVES:   To evaluate in a general population, the relationships between dysglycaemia, insulin resistance and metabolic variables, and heart rate, heart rate recovery and heart rate variability. METHODS:   Four hundred and forty-seven participants in the Data from an Epidemiological Study on the Insulin Resistance syndrome (DESIR) study were classified according to glycaemic status over the preceding 9 years. All were free of self-reported cardiac antecedents and were not taking drugs which alter heart rate. During five consecutive periods: rest, deep breathing, recovery, rest and lying to standing, heart rate and heart rate varability were evaluated and compared by ANCOVA and trend tests across glycaemic classes. Spearman correlation coefficients quantified the relations between cardio-metabolic risk factors, heart rate and heart rate varability. RESULTS:   Heart rate differed between glycaemic groups, except during deep breathing. Between rest and deep-breathing periods, patients with diabetes had a lower increase in heart rate than others (P(trend) < 0.01); between deep breathing and recovery, the heart rate of patients with diabetes continued to increase, for others, heart rate decreased (P(trend) < 0.009). Heart rate was correlated with capillary glucose and triglycerides during the five test periods. Heart rate variability differed according to glycaemic status, especially during the recovery period. After age, sex and BMI adjustment, heart rate variability was correlated with triglycerides at two test periods. Change in heart rate between recovery and deep breathing was negatively correlated with heart rate variability at rest, (r=-0.113, P < 0.05): lower resting heart rate variability was associated with heart rate acceleration. CONCLUSIONS:   Heart rate, but not heart rate variability, was associated with glycaemic status and capillary glucose. After deep breathing, heart rate recovery was altered in patients with known diabetes and was associated with reduced heart rate variability. Being overweight was a major correlate of heart rate variability

Propensity score weighting plus an adjusted proportional hazards model does not equal doubly robust away from the null

Recently it has become common for applied works to combine commonly used survival analysis modeling methods, such as the multivariable Cox model, and propensity score weighting with the intention of forming a doubly robust estimator that is unbiased in large samples when either the Cox model or the propensity score model is correctly specified. This combination does not, in general, produce a doubly robust estimator, even after regression standardization, when there is truly a causal effect. We demonstrate via simulation this lack of double robustness for the semiparametric Cox model, the Weibull proportional hazards model, and a simple proportional hazards flexible parametric model, with both the latter models fit via maximum likelihood. We provide a novel proof that the combination of propensity score weighting and a proportional hazards survival model, fit either via full or partial likelihood, is consistent under the null of no causal effect of the exposure on the outcome under particular censoring mechanisms if either the propensity score or the outcome model is correctly specified and contains all confounders. Given our results suggesting that double robustness only exists under the null, we outline two simple alternative estimators that are doubly robust for the survival difference at a given time point (in the above sense), provided the censoring mechanism can be correctly modeled, and one doubly robust method of estimation for the full survival curve. We provide R code to use these estimators for estimation and inference in the supplementary materials