From secular stagnation to robocalypse? Implications of demographic and technological changes

Los cambios demográficos y una nueva ola de innovación y de automatización son dos de las principales tendencias estructurales que configurarán el escenario macroeconómico en las próximas décadas. Utilizando un modelo de equilibrio general con una sencilla estructura demográfica, investigamos los principales mecanismos de transmisión por los cuales la demografía y la tecnología afectan al crecimiento económico. Debido a una disyuntiva entre innovación y automatización, una menor fertilidad y el envejecimiento poblacional generan una reducción en el crecimiento del PIB per cápita y en la participación de los salarios en el PIB. Durante la transición demográfica, la medida en la que el crecimiento y la participación de los factores se ven afectados depende de las diferentes configuraciones del mercado laboral y de escenarios para la integración de robots en la actividad económica.Demographic change and automation are two main structural trends shaping the macroeconomy in the next decades. We present a general equilibrium model with a tractable life-cycle structure that allows the investigation of the main transmission mechanisms by which demography and technology affect economic growth. Due to a trade-off between innovation and automation, lower fertility and population ageing lead to reductions in GDP per capita growth and the labour income share. During the demographic transition, the extent growth and factor shares are affected depends on alternative labour market configurations and scenarios for the integration of robots in economic activity

Collocation analysis for UMLS knowledge-based word sense disambiguation

BACKGROUND: The effectiveness of knowledge-based word sense disambiguation (WSD) approaches depends in part on the information available in the reference knowledge resource. Off the shelf, these resources are not optimized for WSD and might lack terms to model the context properly. In addition, they might include noisy terms which contribute to false positives in the disambiguation results. METHODS: We analyzed some collocation types which could improve the performance of knowledge-based disambiguation methods. Collocations are obtained by extracting candidate collocations from MEDLINE and then assigning them to one of the senses of an ambiguous word. We performed this assignment either using semantic group profiles or a knowledge-based disambiguation method. In addition to collocations, we used second-order features from a previously implemented approach.Specifically, we measured the effect of these collocations in two knowledge-based WSD methods. The first method, AEC, uses the knowledge from the UMLS to collect examples from MEDLINE which are used to train a Naïve Bayes approach. The second method, MRD, builds a profile for each candidate sense based on the UMLS and compares the profile to the context of the ambiguous word.We have used two WSD test sets which contain disambiguation cases which are mapped to UMLS concepts. The first one, the NLM WSD set, was developed manually by several domain experts and contains words with high frequency occurrence in MEDLINE. The second one, the MSH WSD set, was developed automatically using the MeSH indexing in MEDLINE. It contains a larger set of words and covers a larger number of UMLS semantic types. RESULTS: The results indicate an improvement after the use of collocations, although the approaches have different performance depending on the data set. In the NLM WSD set, the improvement is larger for the MRD disambiguation method using second-order features. Assignment of collocations to a candidate sense based on UMLS semantic group profiles is more effective in the AEC method.In the MSH WSD set, the increment in performance is modest for all the methods. Collocations combined with the MRD disambiguation method have the best performance. The MRD disambiguation method and second-order features provide an insignificant change in performance. The AEC disambiguation method gives a modest improvement in performance. Assignment of collocations to a candidate sense based on knowledge-based methods has better performance. CONCLUSIONS: Collocations improve the performance of knowledge-based disambiguation methods, although results vary depending on the test set and method used. Generally, the AEC method is sensitive to query drift. Using AEC, just a few selected terms provide a large improvement in disambiguation performance. The MRD method handles noisy terms better but requires a larger set of terms to improve performance

Employment fluctuations in a dual labour market

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Employment protection legislation, labor courts, and effective firing costs

In many countries, labor courts play a central role in the determination of firing costs by monitoring and supervising the procedures for dismissals, and, eventually, deciding severance payments mandated by the employment protection legislation (EPL). To get some insights about the impact of labor courts on effective firing costs, we explore a new database that contains information on labor courts' intervention in firings before and after the implementation of significant EPL reforms modifying severance payments and procedures for dismissals. Our results suggest that labor court rulings on economic dismissals did not fully translate the reduction of firing costs mandated by the new EPL to effective firing costs

Combining Evidence, Specificity, and Proximity towards the Normalization of Gene Ontology Terms in Text

Structured information provided by manual annotation of proteins with Gene Ontology concepts represents a high-quality reliable data source for the research community. However, a limited scope of proteins is annotated due to the amount of human resources required to fully annotate each individual gene product from the literature. We introduce a novel method for automatic identification of GO terms in natural language text. The method takes into consideration several features: (1) the evidence for a GO term given by the words occurring in text, (2) the proximity between the words, and (3) the specificity of the GO terms based on their information content. The method has been evaluated on the BioCreAtIvE corpus and has been compared to current state of the art methods. The precision reached 0.34 at a recall of 0.34 for the identified terms at rank 1. In our analysis, we observe that the identification of GO terms in the “cellular component†subbranch of GO is more accurate than for terms from the other two subbranches. This observation is explained by the average number of words forming the terminology over the different subbranches

Employment Expectations and Gross Flows by Type of Work Contract

There is growing interest in understanding firms’ temporary and permanent employment practices and how institutional changes shape them. Using data on Spanish establishments, we examine: (a) how employers adjust temporary and permanent job and worker flows to prior employment expectations, and (b) how the 1994 and 1997 labour reforms promoting permanent employment affected establishments’ employment practices. Generally, establishments’ prior employment expectations are realized through changes in all job and worker flows. However, establishments uniquely rely on temporary hires as a buffer to confront diminishing long-run employment expectations. None of the reforms significantly affected establishments’ net temporary or permanent employment flows.http://deepblue.lib.umich.edu/bitstream/2027.42/40032/3/wp646.pd

Employment protection legislation and labor court activity in Spain

La intervención de los juzgados de lo Social en casos de despido da lugar a que pueda existir una diferencia importante entre las indemnizaciones por despido establecidas por la ley y los costes efectivos de despido (después de su resolución). Además de los costes asociados al procedimiento judicial, están los derivados de la incertidumbre sobre el sentido de la sentencia, que puede declarar el despido improcedente, lo que implica una subida sustancial de las indemnizaciones. En 2010 y 2012 sendas reformas laborales ampliaron la definición de despido objetivo procedente en España. En este artículo se usan datos provinciales sobre sentencias judiciales en casos de despido referidos a períodos anteriores y posteriores a la reforma (2004-2014). En este análisis se tienen en cuenta algunas características provinciales (las condiciones locales del mercado de trabajo, características de los juzgados de lo Social, la prevalencia de conciliaciones judiciales, la congestión judicial) que pueden influir en la selección de casos de despido que acaban siendo resueltos por sentencia judicial. Los resultados indican que, a pesar de las reformas de 2010 y 2012, la proporción de despidos que son declarados procedentes por los juzgados de lo Social no ha aumentado significativamente, aunque ahora muestra una asociación negativa con la tasa de paro local menor que en el periodo anterior a las reformasLabor courts may introduce a significant wedge between “legal” firing costs and “effective” (post-trial) firing costs. Apart from procedural costs, there is uncertainty over judges’ rulings, in particular over the likelihood of a “fair” dismissal ultimately being ruled as “unfair”, which may increase fi ring costs significantly. In 2010 and 2012, reforms of Employment Protection Legislation widened the definition of fair economic dismissals in Spain. In this paper we look at Labor Court rulings on dismissals across Spanish provinces before and after the EPL reforms (2004-2014). We make this comparison taking into account a set of co-variates (local labor market conditions, characteristics of the Labor Courts, pre-trial conciliations, congestion of Labor Courts) which may determine the selection of dismissal cases ruled by Labor Courts. Our results suggest that, despite the 2010 and 2012 EPL reforms, the proportion of economic redundancies being ruled as fair by Labor Courts has not substantially increased, although it is now less negatively associated with the local unemployment rate than in the pre-reform perio

Exploiting MeSH indexing in MEDLINE to generate a data set for word sense disambiguation

<p>Abstract</p> <p>Background</p> <p>Evaluation of Word Sense Disambiguation (WSD) methods in the biomedical domain is difficult because the available resources are either too small or too focused on specific types of entities (e.g. diseases or genes). We present a method that can be used to automatically develop a WSD test collection using the Unified Medical Language System (UMLS) Metathesaurus and the manual MeSH indexing of MEDLINE. We demonstrate the use of this method by developing such a data set, called MSH WSD.</p> <p>Methods</p> <p>In our method, the Metathesaurus is first screened to identify ambiguous terms whose possible senses consist of two or more MeSH headings. We then use each ambiguous term and its corresponding MeSH heading to extract MEDLINE citations where the term and only one of the MeSH headings co-occur. The term found in the MEDLINE citation is automatically assigned the UMLS CUI linked to the MeSH heading. Each instance has been assigned a UMLS Concept Unique Identifier (CUI). We compare the characteristics of the MSH WSD data set to the previously existing NLM WSD data set.</p> <p>Results</p> <p>The resulting MSH WSD data set consists of 106 ambiguous abbreviations, 88 ambiguous terms and 9 which are a combination of both, for a total of 203 ambiguous entities. For each ambiguous term/abbreviation, the data set contains a maximum of 100 instances per sense obtained from MEDLINE.</p> <p>We evaluated the reliability of the MSH WSD data set using existing knowledge-based methods and compared their performance to that of the results previously obtained by these algorithms on the pre-existing data set, NLM WSD. We show that the knowledge-based methods achieve different results but keep their relative performance except for the Journal Descriptor Indexing (JDI) method, whose performance is below the other methods.</p> <p>Conclusions</p> <p>The MSH WSD data set allows the evaluation of WSD algorithms in the biomedical domain. Compared to previously existing data sets, MSH WSD contains a larger number of biomedical terms/abbreviations and covers the largest set of UMLS Semantic Types. Furthermore, the MSH WSD data set has been generated automatically reusing already existing annotations and, therefore, can be regenerated from subsequent UMLS versions.</p

Knowledge-based biomedical word sense disambiguation: comparison of approaches

<p>Abstract</p> <p>Background</p> <p>Word sense disambiguation (WSD) algorithms attempt to select the proper sense of ambiguous terms in text. Resources like the UMLS provide a reference thesaurus to be used to annotate the biomedical literature. Statistical learning approaches have produced good results, but the size of the UMLS makes the production of training data infeasible to cover all the domain.</p> <p>Methods</p> <p>We present research on existing WSD approaches based on knowledge bases, which complement the studies performed on statistical learning. We compare four approaches which rely on the UMLS Metathesaurus as the source of knowledge. The first approach compares the overlap of the context of the ambiguous word to the candidate senses based on a representation built out of the definitions, synonyms and related terms. The second approach collects training data for each of the candidate senses to perform WSD based on queries built using monosemous synonyms and related terms. These queries are used to retrieve MEDLINE citations. Then, a machine learning approach is trained on this corpus. The third approach is a graph-based method which exploits the structure of the Metathesaurus network of relations to perform unsupervised WSD. This approach ranks nodes in the graph according to their relative structural importance. The last approach uses the semantic types assigned to the concepts in the Metathesaurus to perform WSD. The context of the ambiguous word and semantic types of the candidate concepts are mapped to Journal Descriptors. These mappings are compared to decide among the candidate concepts. Results are provided estimating accuracy of the different methods on the WSD test collection available from the NLM.</p> <p>Conclusions</p> <p>We have found that the last approach achieves better results compared to the other methods. The graph-based approach, using the structure of the Metathesaurus network to estimate the relevance of the Metathesaurus concepts, does not perform well compared to the first two methods. In addition, the combination of methods improves the performance over the individual approaches. On the other hand, the performance is still below statistical learning trained on manually produced data and below the maximum frequency sense baseline. Finally, we propose several directions to improve the existing methods and to improve the Metathesaurus to be more effective in WSD.</p

Durvalumab for recurrent or metastatic head and neck squamous cell carcinoma: Results from a single-arm, phase II study in patients with ≥25% tumour cell PD-L1 expression who have progressed on platinum-based chemotherapy

Anticossos; Immunoteràpia; Càncer de cap i collAnticuerpos; Inmunoterapia; Cáncer de cabeza y cuelloAntibodies; Immunotherapy; Head and neck cancerBackground Patients with recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC) progressing on platinum-based chemotherapy have poor prognoses and limited therapeutic options. Programmed cell death-1 (PD-1) and its ligand 1 (PD-L1) are frequently upregulated in HNSCC. The international, multi-institutional, single-arm, phase II HAWK study ( NCT02207530 ) evaluated durvalumab monotherapy, an anti-PD-L1 monoclonal antibody, in PD-L1-high patients with platinum-refractory R/M HNSCC. Patients and methods Immunotherapy-naïve patients with confirmed PD-L1-high tumour cell expression (defined as patients with ≥25% of tumour cells expressing PD-L1 [TC ≥ 25%] using the VENTANA PD-L1 [SP263] Assay) received durvalumab 10 mg/kg intravenously every 2 weeks for up to 12 months. The primary end-point was objective response rate; secondary end-points included progression-free survival (PFS) and overall survival (OS). Results Among evaluable patients (n = 111), objective response rate was 16.2% (95% confidence interval [CI], 9.9–24.4); 29.4% (95% CI, 15.1–47.5) for human papillomavirus (HPV)-positive patients and 10.9% (95% CI, 4.5–21.3) for HPV-negative patients. Median PFS and OS for treated patients (n = 112) was 2.1 months (95% CI, 1.9–3.7) and 7.1 months (95% CI, 4.9–9.9); PFS and OS at 12 months were 14.6% (95% CI, 8.5–22.1) and 33.6% (95% CI, 24.8–42.7). Treatment-related adverse events were 57.1% (any grade) and 8.0% (grade ≥3); none led to death. At data cut-off, 24.1% of patients remained on treatment or in follow-up. Conclusion Durvalumab demonstrated antitumour activity with acceptable safety in PD-L1-high patients with R/M HNSCC, supporting its ongoing evaluation in phase III trials in first- and second-line settings. In an ad hoc analysis, HPV-positive patients had a numerically higher response rate and survival than HPV-negative patients.This study was supported by AstraZeneca