Relevant Research Fields Research Articles

Scanning the Milky Way for 10 years: Discoveries from the Sino-German 6 cm polarization survey of the Galactic plane

<p indent=0mm>Radio continuum polarization observation is a powerful tool to study the properties of the Galactic interstellar medium. By using the 25-m radio telescope of Xinjiang Astronomical Observatories of Chinese Academy of Sciences the Sino-German 6 cm polarization survey of the Galactic plane was carried out by the National Astronomical Observatories of Chinese Academy of Sciences and the Max-Planck-Institute for Radio Astronomy. The observed sky coverage is the Galactic plane in the region from 10° to 230° in the Galactic longitude and within ±5° in the Galactic latitude. The survey is by far at the highest frequency for a Galactic plane polarization survey conducted by a ground-based radio telescope. Through the ten-year efforts by the Chinese and German scientists, the survey revealed the distribution of the total intensity emission and the orientation in the sky plane of the Galactic magnetic fields, which allows us to paint a scroll of the Galaxy with the data obtained with a telescope in China. At such a higher frequency than that of other surveys over the world, the <sc>6 cm</sc> observations experience less Faraday rotations, and are thus able to detect the polarized emission from a further distance. Based on the survey data, we have obtained a series of results on Galactic supernova remnants (SNRs), HII regions and Faraday screens with high rotation measures. Four new Galactic SNRs have been discovered, among which G178.2–4.2 and G25.1–2.3 published in 2011 are the first discovery of Galactic SNRs by a Chinese radio telescope using the first-hand data. Measurements of flux densities, polarization and spectra were performed for more than 70 known SNRs. The polarized emission is observed, for the first time, for the SNRs G16.2–2.7, G69.7+1.0, G84.2–0.8, G85.9–0.6, G205.5+0.5 and G206.9+2.3. The accurate measurements of the <sc>6 cm</sc> flux densities are crucial to determine the spectra of 20 SNRs. Measurements and statistic studies were made for 401 HII regions toward which the flux densities can be precisely estimated. The result complemented the WISE HII region catalog with regards on the extended sources and fixed the mistakes in the commonly used radio HII region catalog. For the diffuse polarized emission, we have detected many new intriguing structures with high Faraday rotation measures which cannot be observed at low radio frequencies because of severe depolarization. These structures, referred to as Faraday screens, do not have total intensity correspondents, indicating the necessity of polarization observations in understanding the Galactic interstellar medium. The <sc>6 cm</sc> survey data have been made public and the results have already generated high impacts on relevant research fields. The project has demonstrated that a medium size telescope such as the <sc>25 m</sc> dish used for the survey is also capable of achieving great science, and the key is to find the niche in this case which is the polarization survey of the Galactic plane. The survey not only produced exciting results on the polarized emission from the Galaxy but also trained next generation radio astronomers who are now active for large facilities such as the Five-hundred-meter Aperture Spherical radio Telescope (FAST) and the Square Kilometre Array (SKA).

Dealloying: An effective method for scalable fabrication of 0D, 1D, 2D, 3D materials and its application in energy storage

Nanomaterials have promising applications in catalysis, filtration, hydrogen storage, sensors, automobile exhaust treatment, and energy storage and conversion, etc. However, scalable and economic fabrication of nanomaterials remains a challenge. In the past century, the world has witnessed successful industrialization of nanoporous Raney nickel in thousands of tons per year by dealloying method. With the advantages of low cost, scalable fabrication and controllable structure, dealloying technique has attracted more attention and gained wider applied in numerous areas. This review attempts to summarize the recent progress in development of dealloying technique, with special emphasis on synthetic materials (0D, 1D, 2D, 3D) and advanced applications, including lithium-ion batteries, lithium-oxygen batteries, lithium-sulfur batteries, lithium-metal batteries, zinc-metal batteries, sodium-ion batteries, magnesium-ion batteries, potassium-ion batteries, aluminum-ion batteries, aluminum-carbon dioxide batteries, and supercapacitors, etc. The advantages, theoretical research, and influence factors of dealloying technique are also analyzed. Besides, key scientific issues and prospective directions of dealloying technique are also discussed. We believe this review may attract more researchers in relevant fields and offer some guide for the future development of dealloying technique.

A Supervised Machine Learning Approach for the Credibility Assessment of User-Generated Content

Consumers increasingly rely on online reviews to assist them in their buying decisions. The rising popularity of e-commerce websites, hotel reviews, and social media has become a relevant research field in recent years. Online reviews affect people’s decisions in their day-to-day life; the fake review impacts both consumers and business organizations. They need to know how different types of consumers prefer consumer feedback, which influences their opinion. Automatic detection of such reviews is a difficult job, provided that the author writes in such a way that it seems like a real review. Previous work has tackled the identification of fake reviews in many fields, including food reviews or company reviews in a restaurant and hotels. In this study, we proposed a fully supervised approach to distinguish opinion spammers in online reviews. In this work, we have used labeled data that can be useful to classify real and fake reviews. We have also implemented various machine learning algorithms for classification on two different datasets (Yelp hotel review dataset, Yelp restaurant review dataset). We have performed the classification task on the features engineered dataset. Our experiment’s measured results show that Logistic regression performs better than other algorithms on most occasions. We may conclude that the presented study contributes to the existing literature with better accuracy from the obtained results.

WHAT’S GOING ON IN ABSORPTIVE CAPACITY STUDIES? RESEARCH FRONTS ON ORGANISATIONAL KNOWLEDGE ABSORPTION

Absorptive capacity (ACAP) is one of the most active themes in knowledge management literature. The topic is extensively mentioned in several relevant research fields, including innovation, organisational learning and strategic management. In this study, we employed bibliographic coupling to analyse the extant academic literature published in order to detect research fronts on the theme. Our sample includes 2,072 papers published in the last four years, which is in line with our basic intent to investigate the latest academic research. Papers included in the core research front highlight the role of ACAP as an organisational ability to assess new valuable knowledge, aiding the development of organisational capabilities. The role of knowledge absorption capacity in alliance networks, open innovation processes, intra-organisational learning, as well as exploratory and exploitative initiatives are the other relevant research fronts identified. We suggest the proposed implications of the analysis as material for further research on the theme.

FASHE: A FrActal Based Strategy for Head Pose Estimation.

Head pose estimation (HPE) represents a topic central to many relevant research fields and characterized by a wide application range. In particular, HPE performed using a singular RGB frame is particular suitable to be applied at best-frame-selection problems. This explains a growing interest witnessed by a large number of contributions, most of which exploit deep learning architectures and require extensive training sessions to achieve accuracy and robustness in estimating head rotations on three axes. However, methods alternative to machine learning approaches could be capable of similar if not better performance. To this regard, we present FASHE, an approach based on partitioned iterated function systems (PIFS) to represent auto-similarities within face image through a contractive affine function transforming the domain blocks extracted only once by a single frontal reference image, in a good approximation of the range blocks which the target image has been partitioned into. Pose estimation is achieved by finding the closest match between fractal code of target image and a reference array by means of Hamming distance. The results of experiments conducted exceed the state of the art on both Biwi and Ponting'04 datasets as well as approaching those of the best performing methods on the challenging AFLW2000 database. In addition, the applications to GOTCHA Video Dataset demonstrate that FASHE successfully operates in-the-wild.

Criticism of the media language: Questions for discussion

The article is devoted to one of the four directions of modern media linguistics — criticism of the media language (CM). The main prerequisites for the design of CM are the logic of the development of modern linguistics, which demonstrates a steady increase in attention to the communicative capabilities of the language realized in different discursive spaces, the movement of active language processes into the media space and the resulting conflict between the traditional idea of speech culture and the new requirements for the effective use of language resources. The author draws attention to the solution of many installation issues that are recorded in the dictionary-directory Medialinguistics (2018). The uniqueness of the research field of the Kyrgyz Republic is presented in the collective monograph Media Linguistics of the Slavic Countries (2020), which is a milestone for Slavic media studies. But the goal of the author of this article is to identify the discussion areas that have already been identified in the relevant research field. The author attempts to present topical, debatable, issues focusing on the previously stated criteria for evaluating media speech: effectiveness, correctness, ethics, aesthetics. The key findings are as follows: 1) the normative concept of media speech is formed in the process of dialogic interaction between the competent professional community “processing the language” and philologists who are able to comprehend the results of this “processing” on the basis of a detailed analysis of the speech situation in the mass media; 2) the most important task of CM is related to the satisfaction “the need for generally understandable, correct language”, which corresponds to the establishment and preservation of national unity and “political and economic integrity of the state” (the idea of N. I. Tolstoy); 3) the most indisputable when recognizing several controversial moments are the criteria for the effectiveness and correctness of the media speech; 4) one of the most serious debatable issues arises in the area of ethical and aesthetic reflection of criticism related to the verbal representation of the comic category in Russian mass media.

EFFECT OF COVID-19 ON SCHOOL EDUCATION SYSTEM: CHALLENGES AND OPPORTUNITIES TO ADOPT ONLINE TEACHING AND LEARNING

Purpose of Study: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), deals with Coronavirus Disease 2019 (COVID-19) has instantly spread worldwide, leading to an episode of intense irresistible pneumonia. The COVID-19 pandemic has created a phenomenal change in educational teaching-learning framework globally. Other than financial and social effects, there is a difficulty in adopting new online education systems by stakeholders of academic institutions.&#x0D; Methodology: The review presented here is based on the platinum open access literature focusing on the adoption of the online education system during the current pandemic situation. This compilation of the findings is based on a systematic review published by the scholars of the relevant field of research targeted to opportunities and challenges in adopting ICT (Information and Communication Technology) and online teaching-learning pedagogy. &#x0D; Main Findings: Specifically, school students need to deal with various sorts of ecological, electronic, and mental battles because of the COVID-19 pandemic. The whole education system from elementary to tertiary level has been imploded during the lockdown time of the COVID-19 in India and worldwide. The New Education Policy (NEP) 2020 has been delivered by the recently renamed Ministry of Education. The approach has given another face to the Online Education System in India.&#x0D; Applications of this study: The finding of the current investigation is a portrayal of opportunities and challenges in receiving the online teaching-learning education system by the public and private educational institutions. It will help in the planning and development of strategies to handle the challenges and opportunities of e-learning during the current global epidemic.&#x0D; Novelty of the study: The authors endeavored to address the web-based learning and teaching in the school training system in the midst of the COVID-19 pandemic. The capacity of offered resources in academic organization effectively changed conventional education into online schooling with the help of virtual classes and other urgent online gadgets in this reliably moving instructive scene.

Knowledge Sharing and Transfer in an Open Innovation Context: Mapping Scientific Evolution

The essence of innovation lies in knowledge, which is why open innovation opens the door to knowledge transfer with agents outside the organization. In order to comprehend the joint scientific trajectory of these two areas of knowledge, the aim of this study is to identify and analyze the main indicators of scientific behavior involved in the research field related to the link between open innovation and knowledge transfer or knowledge sharing concepts through bibliometric and network analysis. The results show clear European leadership in scientific production developed in universities. In addition, the high quality of the main sources of diffusion infers publications of good scientific quality. The most recognized source of knowledge used in new research is directed towards university-company relationships in an open innovation environment. Network analysis related to keywords has allowed us to define the most interesting, relevant fields of research, highlighting the importance acquired by topics such as ‘communication’, ‘inter-organizational context’ and ‘education’, to better focus on future research of the scientific community. It can be concluded that the scientific development of both concepts is an active field in the academic community, and also, that new key terms appear, opening new paths of research.

Research Progress on the Anti-Cancer Molecular Mechanisms of Huaier.

Huaier (Trametes robiniophila Murr), a Chinese traditional herb of medicine, has demonstrated promising curative effects in clinical treatment for various tumors. There are documented experiments showing the biological functions of Huaier with its antineoplastic molecular mechanisms: restraining proliferation and metastasis, arresting cell cycle, inducing apoptosis, pyrosis, and autophagy, anti-intratumoral angiogenesis, attenuating characteristics of tumor stem-like cells, interfering with the function of the tumor-related immune system, reversing drug resistance, and enhancing the sensitivity to chemotherapeutic drugs, etc. In addition, studies suggest that non-coding RNA (ncRNA) acts a pivotal part in cancer occurrence and development, and demonstrates that Huaier adjusts the performance of certain lncRNA (long non-coding RNA) and proceeds to affect the microRNA and its target genes, rendering an anti-tumor effect. Huaier also modulates the expression of lncRNA to attenuate the activity of ncRNA-sponged microRNA and then inhibits the expression of downstream target genes. We summarize and illustrate the experimentally confirmed anti-cancer molecular mechanisms of Huaier, to inspire new ideas for researchers in relevant fields.

Preface

About Srinivas University (Organizer) Srinivas University, Mangalore, is a Private Research University in Mangalore, Karnataka, India established in 2013 by the Karnataka State Act. Srinivas University is the flagship of 18 Srinivas Group of Institutions started by A. Shama Rao Foundation, Mangalore, India, a private Charitable Trust founded in 1988 by an Eminent Chartered Accountant A. Raghavendra Rao. A. Shama Rao Foundation has started many professional colleges in Mangalore which include Srinivas Institute of Medical Sciences and Research Center, Srinivas Institute of Dental Sciences, Srinivas Institute of Technology, Srinivas College of Pharmacy, Srinivas Institute of Nursing Sciences, A Shama Rao Nursing School, Srinivas Integrated Campus, Srinivas College of Hotel Management, Vijayalakshmi Institute of Hospitality Sciences, Srinivas First Grade College, Srinivas School of Engineering, Srinivas Institute of Management Studies, Srinivas College of Physiotherapy, Srinivas School of Business, Srinivas School of Management, Srinivas College of Education, Srinivas Institute of Social Work. About Department College of Computer Science and Information Science is envisioned to other courses which would build the students into enthusiastic quality professionals in the field of Computer Science and Information Technology. The College is located in the heart of Mangalore City, connected with Central Railway Station others excellent learning atmosphere. Students are exposed to a variety of curricular, co-curricular and extra-curricular activities that transform them into dynamic change agents who are able to make a difference by their presence wherever they are. Students from different parts of the country and regions who enroll in the college make it truly inclusive and multi-cultural. The college promotes research in relevant fields of Computer and Information Science also other Ph.D/D.Sc and Post-Doctoral Fellow Programme in accordance with the regulations of the University. About Conference International Conference on Computational Physics in Emerging Technologies (ICCPET’2020) aims to bring together leading Academic Scientists, Researchers, Practitioners, Educators to present, discuss the most recent Innovations, Trends, and concerns as well as practical challenges encountered and solutions adopted in the domain of interest from around the world to exchange, share their experiences and research results on all aspects of Computational Physics. Prospective authors are kindly encouraged to contribute to and help shape the conference through submissions of their research abstracts, papers, e-posters and high quality research contributions describing original and unpublished results of conceptual, constructive, empirical, experimental, or theoretical work in all areas of Computational Physics in Emerging Technologies are cordially invited for presentation at the conference. International Conference on Advances in Computational Physics in Emerging Technologies is the premier interdisciplinary platform for the presentation of new advances and research results in the fields.International Conference on Computational Physics in Emerging Technologies (ICCPET’2020) is the premier interdisciplinary platform for Academicians, Authors, Students, Research Scholars, Scientists and Industry Experts for the presentation of new advanced innovative research ideas and results to share in the field. The more gatherings get shut down due to the growing concern of the Coronavirus Pandemic (COVID-19). So, there may be a chance of entire conference events will take place online for all national and International Participants. We have modern technology support from our university, Which enables us to hold face-to-face Virtual presentations and for a digital event to take place, in lieu of an in-person event. We look forward to bringing together Keynotes Speakers and Participants from all parts of the world in this new virtual format to learn and together. The live online conferences will have the same content as the in-person versions and will maintain the same agenda as originally planned, with minor adjustments to the schedule that are convenient for attendees in different time zones. Replacing the in-person event with a dynamic virtual Presentation will enable us to bring attendees and speakers together in a healthy and productive way.The Location of the conference was Srinivas University, Pandeshwar, Mangalore-575001, Karnataka, India. Entire Conference in Online mode through Cisco Webex Meeting. First 1 Hour inauguration and next 2 hours Invited talk. Discussion and Question and Answer happened through webex Platform. The delegates will present paper from their location through Webex sharing. We had a capacity to accommodate 1000 participants in webex Platform. We had a Internet speed of 50 Mbps. We had continuous stable internet connection. We were able to conduct smoothly virtual conference. For Inauguration there were only 30 members and some participants internet connection was not stable, other than this there was no problem in conducting virtual conference.List of Conference Report, SRINIVAS UNIVERSITY International Conference on Computational Physics in Emerging Technologies, ICCPET 2020 Oral Presentation Guidelines, PRESENTATION SCHEDULE, Editors, The Invoice Address are available in the pdf.

Socionomy and environmental psychology: some common basis

The article consists of a bibliographic review and theoretical-methodological articulation to bring socionomy closer to environmental psychology, a relevant research field for the 21st century, given the contemporary human-environmental crisis. The source selection method and the inclusion and exclusion criteria of literature and articles made it possible to identify common origins for socionomy and environmental psychology, based on a discussion of epistemological foundations that make the proposed approach possible. Although historical and epistemological similarities are evident, only one research report intentionally associating socionomy with environmental psychology was found across the sources consulted. As a heuristic contribution, the authors suggest the use of sociopsychodramatic methods in future studies on environmental psychology.

The Fuzzy Assembly Line Worker Assignment and Balancing Problem

Consideration is given to the assembly line worker assignment and balancing problem (ALWABP) with uncertain task processing times and objective to simultaneously minimize the fuzzy cycle time and the fuzzy smoothness index of the line. After positioning the problem within the relevant research field, we present a genetic algorithm (GA) for its solution. Results over selected benchmarks test problems show the effectiveness of the proposed GA. The results obtained are further supported by a sensitivity analysis that shows the effect of the vagueness (uncertainty) of the task processing times on the uncertainty of the examined optimization criteria.

Reply to: Discussion on “Landslides impact reduction effect by using honeycomb-hole submarine pipeline” by X. Guo, T. Nian, F. Wang, L. Zheng [Ocean Engineering 187 (2019) 106155

This work is a response to the discussion paper by X. Qian, J. Xu, Y. Bai and H.S. Das on our recent paper (Guo et al., 2019a) published in Ocean Engineering. Their attention and recognition of the study are appreciated, and we are grateful to the editor-in-chief for providing this valuable opportunity to further discuss our work in detail. In general, our reply is organized point by point, including the formation mechanism of impact forces on pipelines induced by submarine landslides, drag reduction mechanism of unconventional submarine pipelines (e.g., pipelines with honeycomb holes or streamlined contours), and analysis on the application of unconventional submarine pipelines. It is sincerely hoped that researchers in relevant fields have a multiviewpoint understanding of the evolutionary mechanism of the impact forces on these pipelines impacted by submarine landslides through these discussions.

Drought response of European beech (Fagus sylvatica L.)—A review

European beech (Fagus sylvatica) is the dominant tree species of Central Europe’s natural forests and one of the continent’s most important timber species. This highly competitive species is known to be drought-sensitive and thus may increasingly be threatened by climate change-related heat waves and drought in part of its distribution range. Tree responses and tolerance to drought are complex processes that are best understood by adopting a multi-level analysis spanning from the molecular physiological to the tree and stand levels. Here I review recent progress in our understanding of beech drought responses in all relevant fields of research, notably adjustments in cellular biochemistry, responses of photosynthesis, stomatal regulation and leaf water status, the vulnerability of the hydraulic and phloem systems, adaptive responses of the fine root system, leaf area adjustments, long-term declines in radial growth, and drought-induced tree mortality. A special focus is on population differences in drought tolerance as the basis for the selection of drought-hardier provenances. The evidence from the different research fields is brought together with the aim to develop a multi-disciplinary perception of beech drought response, to identify weak components in the species’ drought response strategy, and to suggest future research efforts to close knowledge gaps.

The role of the gut microbiome in idiopathic Parkinson's disease

In recent years studies have provided increasing evidence suggesting an association between the (gut) microbiome and idiopathic Parkinson's disease (IPD). The aim of this article is to summarize and evaluate existing evidence with respect to the relevance of the (gut) microbiome for IPD. An analysis and critical review of studies in the field of IPD and (gut) microbiome were carried out. The resulting potential perspectives and therapeutic strategies are discussed. Despite partially divergent results between different studies (potentially due to the applied methods and variance in the composition of the investigated cohorts), there is an overlap between studies indicating an association between IPD, the microbiome and microbial metabolites. Nevertheless, the cause-effect relationship between IPD and the microbiome has still not been clarified. Taken together, existing evidence supports apotentially relevant role for the microbiome with respect to typical disease symptoms and pathogenesis of the disease. Over the past 5years there has been an enormous increase in the evidence with respect to the relevance of the microbiome for IPD. While early work in this field was mainly descriptive, new diagnostic methods provide evidence for the underlying mechanisms and the complex interactions between man as the host, the human immune system, the enteric nervous system, gut microbiota and microbial metabolites. Arelatively novel and clinically relevant field of research is how the gut microbiome can influence the success of oral pharmacotherapy and whether substitution of specific microbiome components might be used either for future therapeutic or prophylactic strategies.

Rich Visual Knowledge-Based Augmentation Network for Visual Question Answering

Visual question answering (VQA) that involves understanding an image and paired questions develops very quickly with the boost of deep learning in relevant research fields, such as natural language processing and computer vision. Existing works highly rely on the knowledge of the data set. However, some questions require more professional cues other than the data set knowledge to answer questions correctly. To address such an issue, we propose a novel framework named a knowledge-based augmentation network (KAN) for VQA. We introduce object-related open-domain knowledge to assist the question answering. Concretely, we extract more visual information from images and introduce a knowledge graph to provide the necessary common sense or experience for the reasoning process. For these two augmented inputs, we design an attention module that can adjust itself according to the specific questions, such that the importance of external knowledge against detected objects can be balanced adaptively. Extensive experiments show that our KAN achieves state-of-the-art performance on three challenging VQA data sets, i.e., VQA v2, VQA-CP v2, and FVQA. In addition, our open-domain knowledge is also beneficial to VQA baselines. Code is available at https://github.com/yyyanglz/KAN.

Digital orientalism in Russia

The authors analyze the digital component in the Oriental studies in Russia in the context of key trends and parameters of the growing digitalization of the humanities. The analysis of digitalization in the Oriental studies in Russia is based on the observation of more than 30 Internet resources of the last 10 years. The methodological basis of the work is the analytical and systematic approach to the study using the methods of logical and causal analysis, as well as expert estimates and systematized data. The classification of electronic resources in the relevant field of scientific research is given. Internet resources with a relatively rich database of digitized materials have been analyzed. At the same time, the short period of activity of many Internet resources and the lack of their updating result in a decreased scientific value of these resources. Considering the digital component of the Russian Oriental studies, the development of digital materials complexes takes place, however the digital studies are not conducted. The array of information is fragmented and lacks systematization. The authors conclude that a generalizing system should be created that would activate the available resources and make them work for the development of science.

Research on brain image segmentation based on deep learning

Brain image segmentation algorithm based on deep learning is a research hotspot at present. In this paper, firstly, the significance of brain image segmentation and the content of related brain image segmentation algorithm are systematically described, highlighting the advantages of brain image segmentation algorithms based on deep learning. Then, this paper introduces current brain image segmentation algorithms based on deep learning from three aspects: the brain image segmentation algorithms based on problems existent to brain image, the brain image segmentation algorithms based on prior knowledge guidance and the application of general deep learning models in brain image segmentation, so as to enable researchers in relevant fields to understand current research progress more systematically. Finally, this paper provides a general direction for the further research of brain image segmentation algorithm based on deep learning.

A framework for clinical and translational research in the era of rigor and reproducibility.

Rigor and reproducibility are two important cornerstones of medical and scientific advancement. Clinical and translational research (CTR) contains four phases (T1-T4), involving the translation of basic research to humans, then to clinical settings, practice, and the population, with the ultimate goal of improving public health. Here we provide a framework for rigorous and reproducible CTR. In this paper we define CTR, provide general and phase-specific recommendations for improving quality and reproducibility of CTR with emphases on study design, data collection and management, analyses and reporting. We present and discuss aspects of rigor and reproducibility following published examples of CTR from the literature, including one example that shows the development path of different treatments that address anaplastic lymphoma kinase-positive (ALK+) non-small cell lung cancer (NSCLC). It is particularly important to consider robust and unbiased experimental design and methodology for analysis and interpretation for clinical translation studies to ensure reproducibility before taking the next translational step. There are both commonality and differences along the clinical translation research phases in terms of research focuses and considerations regarding study design, implementation, and data analysis approaches. Sound scientific practices, starting with rigorous study design, transparency, and team efforts can greatly enhance CTR. Investigators from multidisciplinary teams should work along the spectrum of CTR phases, and identify optimal practices for study design, data collection, data analysis, and results reporting to allow timely advances in the relevant field of research.

The ability trap: reductionist theorising about academic ability and the ramifications for education policy and school-based practice

ABSTRACT The paper argues that there is a reductive logic inherent in conceptualisations of academic ability in some Western education research as currently configured. Effective interrogation of this concept necessitates consideration across relevant fields of research, as outlined in three areas of critique: that research on educational stratification can adopt a contradictory stance with respect to conceptualising academic ability and defer to innate cognitive ability in pupil test data while denouncing this elsewhere; that cultural reproduction theory is itself a powerful social construction with ramifications for the possibility of equal learning opportunities for all; and that a narrow focus on educational stratification reifies instrumental outcomes, devaluing some of the broader purposes of education. It is argued that these reductive tendencies have ramifications for education policy and school-based practices. A lack of focus on, and clarity about, the concept of academic ability warrants more holistic conceptualising, which draws on methodological pluralism.