Data Revisions Research Articles

An adaptive confidence-based data revision framework for Document-level Relation Extraction

Noisy annotations have become a key issue limiting Document-level Relation Extraction (DocRE). Previous research explored the problem through manual re-annotation. However, the handcrafted strategy is of low efficiency, incurs high human costs and cannot be generalized to large-scale datasets. To address the problem, we construct a confidence-based Revision framework for DocRE (ReD), aiming to achieve high-quality automatic data revision. Specifically, we first introduce a denoising training module to recognize relational facts and prevent noisy annotations. Second, a confidence-based data revision module is equipped to perform adaptive data revision for long-tail distributed relational facts. After the data revision, we design an iterative training module to create a virtuous cycle, which transforms the revised data into useful training data to support further revision. By capitalizing on ReD, we propose ReD-DocRED, which consists of 101,873 revised annotated documents from DocRED. ReD-DocRED has introduced 57.1% new relational facts, and concurrently, models trained on ReD-DocRED have achieved significant improvements in F1 scores, ranging from 6.35 to 16.55. The experimental results demonstrate that ReD can achieve high-quality data revision and, to some extent, replace manual labeling.11The ReD-DocRED is available at https://github.com/jc4357/ReD-DocRED.

Trends and cycles during the COVID-19 pandemic period

We perform several trend-cycle decompositions through the lens of two unobserved components models, herein estimated for Portugal and the euro area. Our procedure copes with the COVID-19’s consequences by explicitly considering potentially larger second moments during that period. This is achieved through a set of pandemic-specific shocks affecting only the 2020–21 period and embedded into estimation through a piecewise linear Kalman filter. Our methodology generates negligible historical revisions in key smoothed variables when the sample period is expanded until 2021:4, since pandemic shocks absorb a great deal of data volatility with minimal impacts on filtered data revisions or estimated parameters. Furthermore, non-pandemic shock volatility remains largely unaffected by the pandemic period. Innovations affecting the cycle in our preferred model are the key propellers of GDP developments during the COVID-19 pandemic period.

The Productivity Slowdown in Advanced Economies: Common Shocks or Common Trends?

This paper reviews advanced‐economy productivity developments in recent decades. We focus primarily on the facts about, and explanations for, the mid‐2000s labor‐productivity slowdown in large European countries and the United States. Slower total factor productivity (TFP) growth was the proximate cause of the slowdown. This conclusion is robust to measurement challenges including the role of intangible assets, rankings of productivity levels, and data revisions. We contrast two main narratives for the stagnating TFP frontier: The shock of the Global Financial Crisis; and a common slowdown in TFP trends. Distinguishing these two empirically is hard, but the pre‐recession timing of the U.S. slowdown suggests an important role for the common‐trend explanation. We also discuss the unusual pattern of labor productivity growth since the start of the Covid‐19 pandemic. Although it is early, there is little evidence so far that the large pandemic shock has changed the slow pre‐pandemic trajectory of labor‐productivity growth.

Contributing Factors and Challenges in Mastering Academic Writing Skills: Multiple Case Studies of Deaf Students in Inclusive Universities in Indonesia

The purpose of this research is to describe the challenges and factors causing difficulties of deaf students in mastering writing skills at inclusive universities in Indonesia. This research is focused in Central Java province because of the more universities are considered as inclusive universities. This research was conducted in September-December 2022. The subjects in this research were selected using the purposive sampling method. Based on these limits, 35 Deaf students from six inclusive universities were obtained as respondents. The data collection techniques used questionnaires, observations, interviews, and concentrated discussions. Furthermore, the data analysis steps undertaken consisted of: (a) data analysis, (b) data revision, and (c) data verification. The results of this research concluded that the challenges experienced by students were broadly related to: (a) difficulty in mastering vocabulary, (b) understanding punctuation, and (c) difficulty if mastering complex sentences. As for more specifically related to academic text writing skills, the obstacles experienced by students including: (a) composing effective sentences, (b) developing paragraphs, (c) paraphrasing techniques, (d) writing academic texts in accordance with linguistic rules, and (e) writing bibliography. Furthermore, factors causing the occurrence of the obstacles in the mastery of academic text writing skills including: (a) unaccessible learning resources, (b) less effectively interwoven communication during lectures, and (c) different sentence structure in Sign Language (Bisindo) with Indonesian sentence structure.

U.S. Double-Dip Recessions: Do Data Revisions and Data Sources Matter?

U.S. Double-Dip Recessions: Do Data Revisions and Data Sources Matter?

KEMENARIKAN MEDIA PEMBELAJARAN BERBASIS TEACHMINT PADA MATA KULIAH MANAJEMEN PENDIDIKAN MAHASISWA PENDIDIKAN SEKOLAH DASAR

The aim of this research is to evaluate the feasibility, usefulness and efficacy of Teachmint-based learning resources in the Unimed PGSD Department of Educational Materials Management course using classroom management strategies. The ADDIE model—analysis, design, development, implementation, and evaluation—was used in this research and development project. In terms of product validity, the results of data revision and validation from media experts obtained a percentage of 84.35 in the very feasible category, while data validation findings from material experts obtained a percentage of 73.21% which was included in the feasible category. In terms of beauty, 91.60% of the results met the very attractive criteria. In terms of efficacy, students scored an average of 57.6 before the test and an average of 88.8 after the test. The results of the average value show that there are factors that influence the use of Teachmint-based learning resources.

How Well Does Uncertainty Forecast Economic Activity?

AbstractWe evaluate the forecasting ability of several popular measures of uncertainty. We construct new real‐time versions of both macro‐economic and financial uncertainty, and analyze them together with their ex post counterparts. We find some explanatory power in all uncertainty measures, with relatively good performance by ex post macro‐economic and financial uncertainty. However, real‐time versions perform only about as well as other uncertainty measures such as economic policy uncertainty (EPU), a finding we relate to data revisions in the construction of ex post uncertainty. Real‐time data and estimation considerations are highly consequential, owing to look‐ahead bias. Real‐time uncertainty forecasts real‐time outcome variables better than it forecasts ex post revised outcome variables.

Чат-бот как способ поддержки жертв школьной травли

<p style="text-align: justify;">This article is devoted to an overview of the sources on therapeutic chatbots, as well as a description of the problem of creating an anti-bullying chatbot. Most chatbots work on the basis of cognitive-behavioral psychotherapy and are aimed at preventing depressive vessels in adults. There are no anti-bullying chatbots yet. There are at least two reasons: the exceptional situation of bullying and the legal aspects of working with teenagers. The specificity of the bullying situation is working with the patient in real life and health conditions. Trauma-focused Cognitive Behavioral Therapy is the most appropriate method of dealing with victims of school transportation. The legal aspect includes the signing of a data revision resolution and the status of a minor in the conclusion of legal negotiations. The article proposes the idea of an author's chatbot, also based on Cognitive Behavioral Therapy and psychological first aid. The author's dialogue agent includes three blocks: work on emotional manifestations, psychoeducation and acute stress relief. In total, the algorithm includes five emotional channels - four dysfunctional and single-functional. The severity of emotional disturbances is measured on a five-point scale and a mood log, by detecting which you can track the effectiveness of the chatbot. A chatbot cannot implement all the functions of therapy, but it can help reduce the level of emotional stress.</p>

From leaves to labels: Building modular machine learning networks for rapid herbarium specimen analysis with LeafMachine2.

Quantitative plant traits play a crucial role in biological research. However, traditional methods for measuring plant morphology are time consuming and have limited scalability. We present LeafMachine2, a suite of modular machine learning and computer vision tools that can automatically extract a base set of leaf traits from digital plant data sets. LeafMachine2 was trained on 494,766 manually prepared annotations from 5648 herbarium images obtained from 288 institutions and representing 2663 species; it employs a set of plant component detection and segmentation algorithms to isolate individual leaves, petioles, fruits, flowers, wood samples, buds, and roots. Our landmarking network automatically identifies and measures nine pseudo-landmarks that occur on most broadleaf taxa. Text labels and barcodes are automatically identified by an archival component detector and are prepared for optical character recognition methods or natural language processing algorithms. LeafMachine2 can extract trait data from at least 245 angiosperm families and calculate pixel-to-metric conversion factors for 26 commonly used ruler types. LeafMachine2 is a highly efficient tool for generating large quantities of plant trait data, even from occluded or overlapping leaves, field images, and non-archival data sets. Our project, along with similar initiatives, has made significant progress in removing the bottleneck in plant trait data acquisition from herbarium specimens and shifted the focus toward the crucial task of data revision and quality control.

Sharing communication insights of the citizen science program Plastic Pirates—best practices from 7 years of engaging schoolchildren and teachers in plastic pollution research

Engaging the general public in research processes through citizen science allows for innovative scientific studies and makes science accessible to the general public. Effective communication strategies are crucial for the success of such initiatives. The citizen science program Plastic Pirates investigated the plastic pollution of rivers and implemented a variety of communication strategies with participating schoolchildren, teachers, and youth groups (e.g., sport associations, scouts or educational vacation programs, representing approximately 6% of participating groups). These were continuously revised and adapted since its start in 2016. Without time-efficient communication and strategies to keep track of conversations, it would not have been possible to achieve the scientific and educational goals of the program, i.e., to help teachers increase the environmental awareness and scientific literacy of their schoolchildren, and to produce peer-reviewed articles based on the collected citizen science data. Communication within the Plastic Pirates program was divided into four distinct phases: 1) recruiting and motivating participants, 2) coordination and guidance of participants, 3) data reception and revision, and 4) sharing updates and results. Some of the obstacles that had to be overcome to achieve successful communication were e.g., time constraints to obtaining scientific data from the participants, the time lag between the active involvement of the participants and the actual data analysis and publication of results, and limited personnel resources available for communication efforts. Our recommendations for other citizen science practitioners include regular and transparent communication with the participants regarding their contribution, the use of adequate and various communication channels, shifting the workload from the participants to the coordinating team of a citizen science initiative, as well as offering feedback on the research findings to the citizen scientists, thereby disseminating the results of the program.

Employment reconciliation and nowcasting

SummaryWe construct a latent employment estimate for the United States, which both reconciles the information from separate payroll and household surveys and incorporates the preliminary data revision process of the payroll data. We find that our reconciled latent employment series looks somewhat different than the initial release of payroll employment and is closer to the fully revised data that is benchmarked to a near census of employment. A real‐time exercise, however, suggests that the reconciled employment estimate is remarkably similar to the initial release of payroll employment with near zero weight on the household survey information.

Multidisciplinary characterization of the new species Copemetopus mystakophoros and its symbionts with a proposal for the new class Copemetopea (Alveolata: Ciliophora)

Abstract The history of the genus Copemetopus is tortuous and studded with several misattributions. It was erected by Villeneuve-Brachon in 1940 after the discovery of Copemetopus subsalsus in saline ponds along the French coast of the Mediterranean Sea near Sète and associated with the class Heterotrichea in the family Metopidae, close to Bryometopus. After a long series of systematic revisions, it is now clear that Copemetopus is not a heterotrich and that it falls in the subphylum Intramacronucleata. Nevertheless, a lot more work is needed to fix the complex taxonomic status of the genus, which lacks a precise taxonomic collocation (it is presently referred to as incertae sedis). In the present study focused on a multidisciplinary and detailed description of a new species, of the genus, Copemetopus mystakophoros sp. nov., we also propose the erection of the new class, Copemetopea cl. nov. After careful literature and data revision, we believe that members of Copemetopus require a higher-ranked taxon in the phylum Ciliophora, given their molecular and morphological peculiarities.

Practicality of Smart Apps Creator-based Instructional Media on 2D Animation Subject

Based on the results of observations at Vocational high School Pasundan 1 of Serang City (SMK 1 Pasundan Serang City), some of them do not meet the requirements for mastery learning outcomes, students find it difficult to digest animation lessons, and the teacher's limited ability to make media. Anticipating these obstacles requires an interesting new learning media that can generate students' imagination and creativity, one of which is learning media based on smart app creators. This study aims to find out how the process of developing learning media for Smart Apps Creator, to find out from the development of learning media in 2D Animation subjects that will be used in the learning process and to find out interactive learning media based on Smart Apps Creator in 2D Animation subjects at SMK 1 Pasundan which will be used for the teaching and learning process. This method used Research and Development (R&D). Research through use identification of potential and problems, data collection, product design, design validation, revision, product testing, revision, trial, revision and mass production to produce a final product. The trial was conducted on 24 students of class XI SMK Pasundan 1 Serang City. The assessment of the 4 validators of the Interactive Learning Media, which is 90%, shows that the Interactive Learning Media is very valid to be used as a learning resource. The results of the assessment of 24 students that Interactive Learning Media has a practicality value of 89.30%, it can be said that the level of practicality of Interactive Learning Media is very practical and very well stated.

New data, new results? How data sources and vintages affect the replicability of research

Macroeconomic variables like unemployment, inflation, trade, or GDP are not set in stone: they are preliminary estimates that are constantly revised by statistical agencies. These data revisions, or data vintages, often provide conflicting information about the size of a country’s economy or its level of development, reducing our confidence in established findings. Would researchers come to different conclusions if they used different vintages? To answer this question, I survey all articles published in a top political science journal between 2005 and 2020. I replicate three prominent articles and find that the use of different vintages can lead to different statistical results, calling into question the robustness of otherwise rigorous empirical research. These findings have two practical implications. First, researchers should always be transparent about their data sources and vintages. Second, researchers should be more modest about the precision and accuracy of their point estimates, since these estimates can mask large measurement errors.

The Productivity Slowdown in Advanced Economies: Common Shocks or Common Trends?

This paper reviews advanced-economy productivity developments in recent decades. We focus primarily on the facts about, and explanations for, the mid-2000s labor-productivity slowdown in large European countries and the United States. Slower total factor productivity growth was the proximate cause of the slowdown. This conclusion is robust to measurement challenges including the role of intangible assets, rankings of productivity levels, and data revisions. We contrast two main narratives for the stagnating productivity frontier: The shock of the Global Financial Crisis; and a common slowdown in productivity trends. Distinguishing these two empirically is hard, but the pre-recession timing of the U.S. slowdown suggests an important role for the common-trend explanation. We also discuss the unusual pattern of productivity growth since the start of the Covid-19 pandemic. Although it is early, there is little evidence so far that the large pandemic shock has changed the slow pre-pandemic trajectory of productivity growth.

Is everything correct? The formation enthalpy estimation and data revision of nitrate and perchlorate salts

In modern searches for the structure of high-energy-density compounds with high operational,detonation, and physicochemical characteristics, a special place belongs to salts, which have anumber of significant advantages over neutral compounds. The development of this area ofHEDM is hampered by the lack of effective calculation schemes for estimating the enthalpy offormation DHf0 of salts, as a key parameter in assessing the prospects for their use. Based on theauthor's method (MICCM), which is superior in accuracy to currently available calculationmethods, the enthalpies of formation of various salts of nitrates and perchlorates for a promisingclass of high-energy amino-1,2,4-triazoles are calculated and the accuracy of calculations isestimated by other methods. Relationships between the thermochemical characteristics of saltsdepending on various cations are considered. Among the considered compounds, calculations ofthe enthalpies of salts of three amino-1,2,4-triazoles showed a significant discrepancy with theexperimental data. Calculations DHf0of salts were performed using three methods: volume-base thermodynamic(Jenkins/Bartlett method), the method of adding of ions contributions (MAIC, Matyushin'smethod), and the method of ions and cocrystals contribution mixing (MICCM, Khakimov'smethod). Calculations by the MICCM method were carried out on the basis of quantumchemistry methods (when estimating the enthalpies of formation in the gas phase) and themethod of atom-atom potentials (AAP) when calculating the enthalpy of sublimation of salts. Wehave optimized all the structures in the gas phase using the Becke three hybrid exchange andLee-Yang-Parr correlation functional with Grimme's dispersion correction, B3LYP-D2, and aug-cc-pVDZ basis set using the Gaussian16 software. The AAP calculations were performed usingthe FitMEP software packages (for adjusting the charges of the molecular electrostatic potential)and PMC (for the procedure for constructing crystal packings and searching for optimal ones).

Evaluation and indirect inference estimation of inattentive features in a New Keynesian framework

AbstractWe test the standard New Keynesian (NK) dynamic stochastic general equilibrium (DSGE) model with and without inattentiveness features, where inattentiveness is modeled either in the form of sticky information (SI) or imperfect information (IF) data revision. All models are estimated and tested by indirect inference. The estimated model with sticky information somewhat outperformed the estimated NK model with full‐information rational expectation (FIRE), though both passed the test easily, while the model with IF data revision was strongly rejected.

Does Real‐Time Macroeconomic Information Help to Predict Interest Rates?

AbstractWe analyze the predictive ability of real‐time macroeconomic information for the yield curve of interest rates. We specify a mixed‐frequency macro‐yields model in real time that incorporates interest rate surveys and treats macroeconomic factors as unobservable components. Results indicate that real‐time macroeconomic information is helpful to predict interest rates, and that data revisions drive a superior predictive ability of revised macro data over real‐time macro data. We also find that interest rate surveys can have significant predictive power over and above real‐time macroeconomic variables.

Measuring macroeconomic uncertainty: A cross-country analysis

This paper constructs internationally consistent measures of macroeconomic uncertainty. Our econometric framework extracts uncertainty from revisions in data obtained from standardized national accounts. Applying our model to post-WWII real-time data, we estimate macroeconomic uncertainty for 39 countries. The cross-country dimension of our uncertainty data allows us to study the impact of uncertainty shocks under varying degrees of employment protection legislation. Our empirical findings suggest that the effects of uncertainty shocks are stronger and more persistent in countries with low employment protection compared to countries with high employment protection. These empirical findings are in line with a theoretical model under varying firing cost.

Annual estimates of global and national CO2 emissions from fossil fuels: Tracking revisions to the United Nations energy statistics database input energy data

Abstract Estimates of global and national emissions of carbon dioxide (CO2) are important for scientific understanding and public policy on global climate change. Estimates published annually often see revisions of estimates from previous years. Revisions of data on CO2 emissions reflect revisions of the energy data from which CO2 emissions are estimated. Learning is taking place as missing values are compiled, estimated values are revised, and data management systems are updated. Revisions are a frequent feature of the database. Revisions are widespread among countries, commodities, and transactions. We have examined 11 annual reports of the United Nations Energy Statistics Database (those published from 2010 to 2020) to see in the detailed statistics what values are being changed and what are the magnitudes and patterns of change. They are most common in recent years, among developed countries, and among data on liquid fuels. Revisions are generally small and there are no indications of systematic manipulation or bias. Revisions of specific numbers are believed to represent improvements in accuracy but lack of revisions does not point toward accuracy. This examination of revisions does not permit by itself a quantitative estimate of the data uncertainty but it does suggest that the estimates of global and national totals of CO2 emissions are generally consistent and that both absolute values and trends are reliable over time and sufficiently accurate for scientific understanding and public policy.