43569 research outputs found
Sort by
The common behavior effect in norm learning: when frequent observations override the behavior of the majority
No full textPrior research suggests that descriptive norms correspond to what most people do-the "behavior of the majority." We examine norm perception in situations where the behavior of the majority differs from the most frequently observed behavior-the "common behavior." In environments where individuals learn descriptive norms through repeated observations of a reference group, we propose that perceived norms align more closely with the common behavior than with the behavior of the majority. Consequently, individuals are more likely to follow the common behavior, even when it differs from what most people do. We argue that this 'common behavior effect' arises from a combination of two factors: the structure of the information environments in which the behavior of the majority and the common behavior differ, and imperfect source memory of the observed behaviors. We provide evidence for the basic phenomenon and test two moderators in four studies reported in the body of the article and two ancillary studies reported in the appendix. These findings are important for our understanding of social norms, because they challenge the assumption that norms simply reflect the behavior of the majority. They also cast light on phenomena such as pluralistic ignorance, majority illusions in online and offline environments or the spread of misinformation on social media. Finally, they have practical implications for how to shape norms in organizations.This work was sup-ported by the European Commission (grants 772268 and MCIN/AEI/10.13039/501100011033 to G.L.M.), the Agencia Estatal de Investigación, Spain (grants PID2019-105249GB-I00 and PID2022-137908NB-I00 to G.L.M.; PID2023-152226NB-I00 to T.K.A.W; PID2022-140026NB-I00 to R.H), the Fundación BBVA, Spain (Grant G999088Q to G.L.M.), the Barcelona School of Economics (grant CEX2019-000915-S to G.L.M.), the Instituto Nacional de Ciberseguridad (Grant INCIBE-CYBERTHREAT C115/23 to R.H.) and the ICREA Academia (grant to G.L.M). Guillem Pros Rius provided excellent research assistance with programming for Study 2
Occupational recognition and immigrant labor market outcomes
No full textIn this paper, we analyze how the formal recognition of immigrants' foreign occupational qualifications affects their subsequent labor market outcomes. The empirical analysis is based on a novel German data set that links respondents' survey information to their administrative records, allowing us to observe immigrants at monthly intervals before, during and after their application for occupational recognition. Our findings show substantial employment and wage gains from occupational recognition. After three years, the full recognition of immigrants' foreign qualifications increases their employment rates by 24.5 percentage points and raises their hourly wages by 19.8 percent relative to immigrants without recognition. We show that the increase in employment is largely driven by a higher propensity to work in regulated occupations. Relating our findings to the economic assimilation of immigrants in Germany, we further document that occupational recognition leads to substantially faster convergence of immigrants' earnings to those of their native counterpartsHerbert Brücker gratefully acknowledges support by the German Research Foundation (Deutsche Forschungsgemeinschaft) in the priority program SPP 1764 ("The German Labor Market in a Globalized World"). Albrecht Glitz gratefully acknowledges financial support from the Spanish Ministerio de Economía y Competitividad (through the Severo Ochoa Programme for Centres of Excellence in R&D [SEV-2015-0563] and project ECO2014-52238-R) and from the Spanish Ministerio de Ciencia, Innovación y Universidades (project ECO2017-83668-R [AEI/FEDER, UE] and Ramón y Cajal grant RYC-2015-18806). He also thanks the German Research Foundation for funding his Heisenberg Fellowship (GL 811/1-1) and Alexandra Spitz-Oener for hosting him at Humboldt University of Berlin from October 2014 to December 2016
¿Públicos o privados?: un análisis comparado de los modelos de gestión de los centros de internamiento de extranjeros en España y Reino Unido y su influencia en las condiciones de vida de los detenidos
No full textTreball de Fi de Grau en Criminologia i Polítiques Públiques de Prevenció. Curs 2024-2025Tutora: Cristina Güerri FernándezEste trabajo de fin de grado realiza un análisis comparado de los modelos de gestión de los centros de internamiento de extranjeros (CIEs en España e IRCs en Reino Unido) y su influencia en las condiciones de vida de los detenidos, cuestionando los argumentos tradicionales a favor de la privatización. La metodología es cualitativa-comparativa, utilizando datos secundarios de informes oficiales del Mecanismo Nacional de Prevención y HM Chief Inspector of Prisons, así como de organizaciones no gubernamentales y del Comité Europeo para la Prevención de la Tortura y de las Penas o Tratos Inhumanos o Degradantes.
España opera con un modelo público con servicios externalizados, mientras que Reino Unido ha privatizado la gestión integral de todos sus IRCs a empresas de seguridad. Los resultados muestran que, aunque ambos sistemas enfrentan desafíos estructurales inherentes a la detención migratoria, el modelo de gestión modula la forma en que se manifiestan. La privatización en Reino Unido se asocia con la reducción de personal para ahorrar costes, una calidad inconsistente en los servicios y la explotación de la mano de obra cautiva de los detenidos. Se respalda la preocupación por la falta de transparencia y la disipación de la responsabilidad estatal en el modelo privado
The Interplay between Learning Design and Learning Analytics Indicators in Higher Education
No full textLes institucions d'educació superior generen grans quantitats de dades; tanmateix, l'adopció de tecnologies i pràctiques per analitzar sistemàticament aquestes dades continua sent fragmentada. Tradicionalment, els esforços institucionals s'han centrat en aspectes aïllats com la satisfacció dels estudiants, el rendiment acadèmic, l'ús de plataformes digitals o les metodologies actives d'aprenentatge, cosa que ha portat a un enfocament desarticulat en l'anàlisi de les dades educatives. L'aplicació de l'analítica del disseny d'aprenentatge (Learning Design Analytics, LDA), l'analítica d'aprenentatge tradicional (Learning Analytics, LA) i l'analítica institucional (Institutional Analytics, IA) constitueix encara una àrea de recerca poc explorada i metodològicament complexa, ja que la recopilació i interpretació significativa de dades a gran escala presenta reptes tècnics i conceptuals importants. Aquesta tesi doctoral examina una gran universitat espanyola predominantment presencial durant el període comprès entre 2018 i 2022, amb l'objectiu de respondre la següent qüestió: Com pot l'analítica institucional integrar el disseny d'aprenentatge i l'analítica d'aprenentatge (LD-LA) per generar coneixement útil i aplicable en l'educació superior? A través d'una sèrie d'estudis de cas, aquesta recerca ofereix un examen aprofundit de la interacció entre les decisions de disseny pedagògic i els indicadors habitualment utilitzats per avaluar l'experiència dels estudiants. La tesi presenta tres contribucions principals: (1) principis de disseny per a l'analítica institucional que alineen clarament els indicadors LD-LA, (2) indicadors i tècniques específiques per a l'analítica institucional LD-LA, i (3) evidències sobre els beneficis de la integració LD-LA en l'àmbit institucional. Considerant que l'absència d'una perspectiva pedagògica en l'analítica d'aprenentatge pot generar mancances en l'aplicació pràctica dels resultats, aquesta recerca destaca el valor d'un enfocament més integrat i basat en dades per a la presa de decisions institucionals en l'educació superior, assegurant així que els marcs d'analítica d'aprenentatge incorporin adequadament les consideracions del disseny pedagògic per generar coneixements contextualitzats i aplicables.Higher Education Institutions generate vast amounts of data, yet the adoption of technologies and practices to systematically analyze these data remains fragmented. Traditionally, institutional efforts have focused on isolated aspects such as student satisfaction, academic performance, digital platform usage, and active learning methodologies, leading to a disjointed approach to educational data analysis. The application of Learning Design Analytics (LDA), Mainstream Learning Analytics (LA), and Institutional Analytics (IA) remains an underexplored and methodologically complex research area, as large-scale, meaningful data collection and interpretation present both technical and conceptual challenges. This doctoral dissertation examines a large, predominantly face-to-face Spanish university, covering the period from 2018 to 2022, to answer the question: How can Institutional Analytics bridge Learning Design and Learning Analytics (LD-LA) to generate actionable insights in Higher Education? Through a series of case studies, this research provides an in-depth examination of the interplay between pedagogical design decisions and commonly used student indicators. The thesis presents three main contributions: (1) design principles for institutional analytics that align LD-LA indicators, (2) indicators and techniques for LD-LA Institutional Analytics, and (3) evidence about the benefits of LD-LA at the institutional level. Considering that the absence of a pedagogical perspective in LA may lead to gaps in the practical application of insights, the current research highlights the value of a more integrated, data-informed approach to institutional decision-making in Higher Education, ensuring that LA frameworks incorporate pedagogical planning considerations to produce contextually meaningful and actionable insights.Universitat Pompeu Fabra. Doctorat en Tecnologies de la Informació i les Comunicacion
Music identification with audio fingerprinting an industrial perspective
No full textMusic identification is a mature and well-studied field in the Music Information
Retrieval community. In the music industry, it ensures fair distribution of royalties,
which are allocated based on usage, such as plays in live venues or airtime in
broadcasts. This thesis has been conducted as part of an industrial PhD at BMAT, a
company specializing in music monitoring and identification services. This thesis
explores advancements in Audio Fingerprinting (AFP), a core technology for music
identification that identifies audio by matching compact signatures extracted from
audio signals. From their early development in the 2000s, AFP systems have evolved to
address challenges such as robustness to time-frequency modifications, or noise and
speech overlays, for instance. However, scenarios like background music identification
or extreme time-frequency modifications remain challenging for these systems.
To address these gaps, this thesis first introduces a self-contained dataset specifically
designed for broadcast monitoring, featuring TV recordings with a high prevalence of
background music and reference tracks of production music. Alongside this dataset, it
proposes \emph{PeakFP}, a new baseline method tailored for background music
identification. To improve the AFP performance, this thesis explores a two-step
approach combining source separation algorithms with AFP systems. This approach
demonstrates substantial performance improvements in background music
identification, albeit at the cost of computational overhead.
Finally, this thesis presents PeakNetFP, the first hybrid AFP system that integrates the
simplicity and scalability of spectral peaks with the abstraction capabilities of neural
networks. PeakNetFP achieves comparable performance to state-of-the-art models
while being 100 times smaller, offering a scalable and efficient solution for AFP tasks,
including severe time-stretched audio.
Despite being conducted in an industrial setting, this work adheres to the principles of
open science, with all datasets, code, and evaluations made publicly available. This
thesis aims to foster further research in AFP, particularly in underexplored scenarios,
and to contribute to the development of more robust and versatile AFP systems.La identificació musical és un àmbit madur i àmpliament estudiat dins la
comunitat de Recuperació d'Informació Musical (MIR) des de fa molts anys. En la
indústria musical, garanteix una distribució justa de les regalies, que es
reparteixen segons l'ús, com ara reproduccions en esdeveniments en directe o
temps d'emissió en retransmissions. Aquesta tesi s'ha dut a terme en el marc d'un
doctorat industrial a BMAT, una empresa especialitzada en serveis de monitoratge
i identificació musical, i explora els avenços en el camp de l'\emph{Audio
Fingerprinting (AFP)}, una tecnologia clau per a la identificació musical que
reconeix àudios mitjançant la comparació de signatures compactes extretes dels
senyals d'àudio. Des del seu desenvolupament inicial als anys 2000, els sistemes
AFP han evolucionat per afrontar reptes com la robustesa davant modificacions
tempo-freqüencials, soroll i superposicions de veu. No obstant això, escenaris com
la identificació de música de fons o els àudios amb estiraments temporals
extrems continuen sent un desafiament per a aquests sistemes.
Per abordar aquestes limitacions, aquesta tesi presenta primer un conjunt de
dades autocontingut dissenyat específicament per al monitoratge de
retransmissions, amb enregistraments de televisió amb alta prevalença de música
de fons i pistes de música de producció com a referència. Altrament, també
proposa un nou mètode base adaptat per a la identificació de música de fons que
serveix com a sistema de referència. Per millorar el rendiment dels sistemes AFP,
s'explora si les tecnologies existents poden ajudar. En aquest sentit, s'avalua un
enfocament en dues fases que combina algoritmes de separació de fonts amb
sistemes AFP. Aquest mètode mostra millores substancials en la identificació de
música de fons, tot i que en alguns casos implica un cost computacional
significatiu.
Finalment, aquesta tesi presenta PeakNetFP, el primer sistema AFP híbrid que
integra la simplicitat i escalabilitat dels pics espectrals amb les capacitats
d'abstracció de les xarxes neuronals. PeakNetFP aconsegueix un rendiment
comparable als models més avançats del moment, amb una mida 100 vegades
menor, oferint una solució escalable i eficient per a tasques AFP, incloent-hi
àudios amb distorsions temporals extremes.
Tot i que la tesi s'ha desenvolupat en un entorn industrial, segueix els principis de
la ciència oberta, amb tots els conjunts de dades, codi i avaluacions disponibles
públicament. Aquesta tesi té com a objectiu fomentar la investigació futura en
AFP, especialment en escenaris poc explorats, i contribuir al desenvolupament de
sistemes AFP més robusts i versàtils.Programa de Doctorat en Tecnologies de la Informació i les Comunicacion
The genocide that changed the world
No full textData de publicació electrònica: 19-09-2025The question of genocide will never be the same following the Israeli genocide of the Palestinians in Gaza, which is still ongoing after almost two years at the time of writing. This has had a global impact which far exceeds that of other recent cases, and represents a major change in the role of the phenomenon in the international system, with equally transformative significance for its academic study. This article examines the distinctive features of the Gaza case, its consequences and the issues of conceptualization that it poses. It contends that with Gaza, genocide has moved from the margins to the centre of world politics, so that the assumptions about how it can be prevented which prevailed in the previous period are no longer relevant. It also argues that the present conceptual state of the academic genocide studies field is no longer sustainable, and that scholars must revisit its foundations in order to adequately understand the new challenges. In particular, Gaza shows how, even when war and genocide are largely fused, distinct concepts of each are essential for understanding
Modulation of associative memory by emotional item encoding
No full textTreball fi de màster de: Master in Cognitive Systems and Interactive MediaSupervisor: Daniel PachecoAssociative memory, which is the ability to link items with contextual details, is essential for navigating the world and guiding future behavior. Emotional salience, especially of negative valence, is known to influence memory, but its precise effect on associative versus item memory remains debated. While some studies report impairments in context recall for emotional items, others suggest emotion can enhance associative binding under specific conditions. In this study, we investigated how emotional item encoding modulates the ability to recall contextual details during a recognition memory task. Participants encoded images of varying emotional valence (positive, negative, neutral), each paired with a contextual background. At retrieval, they were asked to identify whether an image was old or new, and to recall its original context. Our results show that emotional items were recognised with high accuracy, consistent with prior work, but importantly, we found differential effects on context memory depending on emotional valence. Contrary to the expected “emotional trade-off” effect, context memory for emotional items, particularly negative, was not impaired, and in some cases, enhanced. A follow-up analysis comparing performance of one participant across two me points revealed a statistically significant improvement in associative memory, suggesting that repeated exposure to emotional-context pairings may strengthen context binding. These findings provide behavioral evidence that emotional content can modulate associative memory in complex, and not always disruptive, ways
Design principles of cell-state-specific enhancers in hematopoiesis
No full textDuring cellular differentiation, enhancers transform overlapping gradients of transcription factors (TFs) to highly specific gene expression patterns. However, the vast complexity of regulatory DNA impedes the identification of the underlying cis-regulatory rules. Here, we characterized 64,400 fully synthetic DNA sequences to bottom-up dissect design principles of cell-state-specific enhancers in the context of the differentiation of blood stem cells to seven myeloid lineages. Focusing on binding sites for 38 TFs and their pairwise interactions, we found that identical sites displayed both repressive and activating function as a consequence of cell state, site combinatorics, or simply predicted occupancy of a TF on an enhancer. Surprisingly, combinations of activating sites frequently neutralized one another or gained repressive function. These negative synergies convert quantitative imbalances in TF expression into binary activity patterns. We exploit this principle to automatically create enhancers with specificity to user-defined combinations of hematopoietic progenitor cell states from scratch.This study was financed by grants from the Spanish Ministry of Science, Innovation and Universities MCIU/AEI/10.13039/501100011033 (grant PID2019-108082GA-I00 to L.V.; and grant RYC2021-033860-I cofounded by European Union NextGenerationEU/PRTR to R.M.-C.), the Ministry of Science and Innovation (PID2022-142210NA-I00 funded by MCIN/AEI/10.13039/501100011033 / FEDER, UE to R.M.-C.; and pre-doctoral fellowship PRE2021-097675 funded by MCIN/AEI/10.13039/501100011033 and FSE+ to J.R.). This project has received funding from the European Union's Horizon Europe under the grant agreement no. 101041399 (ERC-StG AI4SYN to L.V.). F.P.P. was supported by the predoctoral program AGAUR-FI grants (2023 FI_I 00776), Joan Oró of the Secretariat of Universities and Research of the Department of Research and Universities of the Generalitat de Catalunya, and the European Social Fund Plus. The authors acknowledge support by the Spanish Ministry of Science and Innovation through the Centro de Excelencia Severo Ochoa (CEX2020-001049-S and MCIN/AEI /10.13039/501100011033) and the Generalitat de Catalunya through the CERCA programme and to the EMBL partnership. We are grateful to the CRG Core Technologies Programme for their support and assistance in this work. Research for this publication has been partially carried out in the Barcelona Collaboratorium for Modelling and Predictive Biology
Loneliness as a public health challenge: a systematic review and meta-analysis to inform policy and practice
No full textLoneliness is a recognized public health risk factor associated with increased morbidity and mortality. However, the effectiveness of interventions targeting loneliness remains unclear—particularly in relation to baseline severity. This systematic review and meta-analysis assessed intervention effectiveness and the influence of baseline severity and intervention characteristics. A total of 25 studies were included, of which 16 randomized controlled trials (RCTs; k = 21) were meta-analyzed. Interventions produced a moderate pooled effect at post-intervention (Hedge’s g = 0.65, 95% CI [0.05, 1.26], p = 0.037), though with high heterogeneity. Sensitivity analyses confirmed a moderate effect (g = 0.55, 95% CI [0.22, 0.88], p = 0.003). Higher baseline loneliness predicted greater intervention effects (b = 0.04, 95% CI [0.02, 0.07], Z = 3.36, p < 0.001), with cognitive-behavioral therapy (CBT) showing the largest effect size (g = 0.73). No significant effects were observed at follow-up. These findings underscore the need for dual strategies: targeted psychological interventions (e.g., CBT) for individuals with severe loneliness, and universal, context-based approaches for the broader population. This aligns with Geoffrey Rose’s distinction between individual-level treatment and population-level prevention and highlights the urgency of embedding loneliness interventions into public health frameworks and policy agendas focused on promoting social connectedness and equity