Big Institutions Research Articles

“I would love to see these big institutions… throwing their weight around”: qualitative findings regarding health and social sector collaborations to address community-level socioeconomic adversity

BackgroundHealth and social sector organizations are increasingly working together to mitigate socioeconomic adversity within their communities. We sought to learn about the motivations, experiences, and perspectives of organizations engaged in these collaborations.MethodsWe conducted semi-structured, 60-minute interviews with 34 leaders from 25 health and social sector organizations between January-April 2021. Interviews explored motivations, benefits and challenges, and ways in which health sector organizations can most effectively address community-level socioeconomic adversity. Interviews were audio recorded and transcribed; themes were coded using Dedoose software.ResultsPartnerships were primarily motivated by mission-driven organizations and key health sector leaders who were interested in addressing root causes of poor health; policies such as certificate of need laws and value-based care incentives that aligned community-level investments with health sector organizations’ financial interests facilitated these efforts. While partnerships were mostly regarded as mutually beneficial ways to increase impact (for the health sector) and resource access (for the social sector), social sector organizations voiced frustrations regarding the outsized expectations, unsustained interest, and lack of partnership from their health sector collaborators. Despite these frustrations, both health and social sector interviewees supported the health sector’s continued involvement in community-level socioeconomic initiatives and expansion of policy and systems efforts.ConclusionsCross-sector, community-level socioeconomic initiatives were mutually beneficial, but social sector organizations experienced more frustrations. Policy and organizational changes within the health sector can further mobilize and sustain support for these efforts.

Employees' Perception towards Pygmalion-Oriented Leaders and Leader-Member Exchange in Commercial Banks

Pygmalion-oriented leaders and Leaders Member Exchange (LMX) are the essential antecedents of employees' perception in an organisation, but they are less examined in prior research. Thus, this study examines the employees' view of Pygmalion-oriented leaders and LMX as it might pose a dyadic presentation. This study followed the positivist epistemology. A descriptive and causal research design has been used in this study. One hundred forty employees from commercial banks participated in this study. Responses were collected using a convenience sampling method. The study used correlation and regression to study the Pygmalion effect and LMX impact in shaping employees' perceptions. The findings of the study postulate that the Pygmalion-oriented leader and positive LMX have a significant impact on shaping the employees' perception. The findings of the study show that the Pygmalion effect and Leader Member Exchange has a considerable impact upon shaping the employees’ perception. This study's findings apply to the Nepalese context, specifically in the banking sector and the banking and financial institutions (BFIs) of Nepal. This study is imperative for accentuating the role of the Pygmalion effect and the essence of LMX in managing the BFIs and other big institutions of Nepal.

Croatian Homeland War Memorial Museums – Exhibiting Urbicides and Concentration Camps

AbstractRecently opened memorial museums and exhibitions in Croatia museumize the “Homeland War” of 1991 to 1995. This article examines the four major institutions, the Museum of the Homeland War in Karlovac as well as three sites in Vukovar: The Memorial Center for the Homeland War, the Memorial Hospital and the Ovčara Memorial Home. This first systematic site analysis compares 1) the overall narratives; 2) how enemy images from World War II are reactivated to demonize “the other”; 3) how women are represented in these war exhibitions; and 4) the topics that are left out. I argue that while there is still no national museum that includes war developments in all of the country, the two big institutions, the Museum in Karlovac and the Center in Vukovar, focus on the “defenders,” as the Croatian fighters are called – while in Karlovac strikingly marginalizing and at the Center completely omitting civilians. War here means (male) soldiers and weapons, while the other two institutions portray individual victims without discussing their biographies. In all sites, Serbs are depicted with reference to World War II: as Chetniks, running “concentration camps” who committed either “urbicide and culturocide” or a “holocaust” against Croats.

Effect of Firms’ Soundness on Shareholders’ Earnings of Listed Firms at the Nairobi Securities Exchange, Kenya

The global changes in the business environment and the increased demand for improved shareholder’s earnings have prompted big firms to re-examine their soundness. During the 2008 global economic crisis, many big institutions experienced challenges like liquidity challenges, poor leverage, and drop in share prices and decline in assets which led to the decline in the earnings of shareholders. current study was therefore necessary to analyse the effect of firm’s soundness on shareholders earnings of listed firms at the Nairobi Securities Exchange. The specific objectives of the study were: To evaluate the effect of liquidity on the shareholders earnings of firms listed at Nairobi securities exchange, Kenya, to establish the effect of firm size on shareholders earnings of firms listed at Nairobi securities exchange, Kenya, to examine the effect of leverage on shareholders earnings of firms listed at Nairobi securities exchange, Kenya and to analyse the effect of firm’s age on shareholders earnings of firms listed at the Nairobi securities exchange, Kenya. This study is expected to assist businesses in comprehending the soundness that must be emphasized in order to avoid financial losses. As a result, it assist in informing the policies of listed companies in terms of liquidity, leverage, and assets, which is a measure of the firm's size. Firms should be able to develop a policy that improves shareholder earnings based on soundness. Finally, it is expected that shareholders and other potential investors will benefit from a clear understanding of the factors that influence earnings per share within the company. The Modigliani and Miller theory, as well as the Agency theory, were used to guide the research. A descriptive research design was used in this study. The study's target population was all listed companies on the Nairobi Securities Exchange over the period 2015 to 2021. The 64 companies were analyzed using the census study. Data had been collected using a secondary data collection sheet. The study employed secondary data obtained from the published financial statements of the respective firms, from the Nairobi Securities Exchange and the Capital Markets Data. A panel regression model was employed in the analysis of data with the aid of the stata version 14. The study found out that Liquidity had a positive significant effect on the shareholders earnings In addition, firms’ size had a significant and positive effect on the shareholders ‘earnings. Moreover, Leverage had a non significant positive effect on the shareholders earnings .The firms’ age on the other hand has a positive and significant effect on the shareholders earnings.
 The study recommends the following based on the findings. First the listed firms should enhance its liquidity by investing more on liquid assets. This should entail more investments in treasury bills, treasury bonds and other liquid stocks. They should also diversify their investments by investing in money markets. Additionally it should enhance its liquidity by controlling its overheads through getting rid of unnecessary expenses. Secondly, the listed firms needs to expand its asset base. As seen from the findings, firms size had a significant effect on the shareholder’s earnings meaning that the higher the size in terms of total assets, the higher the shareholders earnings. Firms should therefore expand its assets base by developing new products for the customers, increasing its customer base while expanding to new markets. Thirdly, the findings also indicate that firm’s age has a significant effect on the shareholder’s earnings. To sustain its performance and shareholder’s earnings, firms that have been in operation for many years compared to the rest should harness on the experience and economies of scale to ensure that they are able to sustain their performance. This should entail a thorough trend analysis of its performance over the years and designing better strategies based on the past challenges and its internal strengths.

Pankaj Garg: A Community Doctor to a Master Innovator to a Global Icon

Pankaj Garg’s story is an interesting one and is a source of inspiration for all physicians and budding innovators. He started his career as a community doctor about two decades back in the year 2001, then changed gears in between to become an avid researcher and innovator. He progressed to become a leading international figure in his field. Garg has exemplified three important points. First, with proper temperament, it is possible to achieve academic excellence and conduct research even in a primary care setting. Second, every specialist should fulfill the role of a family physician as well. While pursuing any specialty, the role of a “general physician” should never be ignored. Third, innovation is a state of mind, and big institutions and well-equipped laboratories with costly gadgets are not a prerequisite to it. This is clearly exemplified by Pankaj Garg’s story that it is possible to excel in research, academics, and clinical work at the global level without any research budget, big institute tag, or the help of government or non-government organizations. Garg has more than 175 publications in high-impact journals. He has 30 innovations to his name, in and outside his field of expertise, all of which have been published in international journals. The innovations include new operative procedures, successful non-operative management, the discovery of new anatomical spaces, new concepts in disease understanding and management, and finding non-operative treatment for diseases for which surgery is routinely performed. It is impressive that seven of his innovations are popularly known by his name - Garg classification, Garg space, Garg protocol, Garg cardinal principles, Garg scoring system, Garg phenomenon, and Garg incontinence scores. Due to 30 innovations done single-handedly, Garg has been certified as a “doctor with maximum innovations” by several record books. Due to his ability to think “out-of-the-box” and his immense contribution to advancements in the field of proctology, he is recognized as a global icon in his field. Garg is a master teacher. He has taught surgical skills and the art of scientific paper writing to hundreds of surgeons and doctors. In spite of limited resources at his disposal, Garg goes out of his way to help poor people. He performs about 30–40% of operations free of cost. He has successfully treated patients from 41 countries and several patients from royal families of the Gulf who offered him lucrative money to move to the Middle East. However, Garg flatly refused all offers because his priority was to serve his country and countrymen first. Hence, a simple doctor working in a small city was never discouraged by the lack of resources, and the fear of working alone in a small set-up and without any help from the government has carved out a tale that can motivate professionals in any corner of the world. Dr. Garg’s story provides immense inspiration to every practicing physician in the country to innovate whether he/she is practicing in a primary healthcare center or a rural area.

Design and Development of Paper Recycling Machine

Abstract: In any big institution,especially educational institutions like schoolsor colleges, generation of large quantity ofwaste papers is quite apparent. And effective use of recycled paper is also possible (craft papers, registers etc). So, instead of disposing off the waste papers into trash, recycling themmakes sense. This not only helps the institute in cost saving but will also ensure its contribution towards the protection of the environment. Designing automatically operated small-scaled paper recycling plant, which can be used in schools and colleges, ensures that a cheap and non-complex methodof production of paper product is guaranteed.Accordingly design of the machine unit has been prepared with all necessary component specifications.

Digital Strategy in Paying Zakat Non-Cash at Baitul Maal Hidayatullah (BMH) Pontianak

Applying e-money and fintech is expected to benefit significantly from accessing various services. Some problems become obstacles in transactions, such as the availability of an internet network so that digital e-money applications can be operated. In addition, there are threats in the form of fraud and hacking from cyberspace that make users worry that it can harm users. This quantitative descriptive research aims to determine how big institutions' opportunities, challenges, strengths, and constraints are in non-cash transactions with SWOT analysis. The data in the research were obtained through observation, questionnaires, interviews, and documentation. The study results show that Baitul Maal Hidayatullah (BMH) institutions have not optimally utilized digital media through payment channels. The SWOT analysis results show that the opportunity for the BMH institution is 2.88, and the strength is 2.50. So that the institution has the potential to seize existing opportunities by choosing a digital strategy in a medium (growing) state, meaning that the institution is in good condition choosing this step. Even though it has not been felt optimally, success has been marked by BMH income from 2019 of Rp. 648,300,529 and 2021 Rp. 799,775,147 increased by a margin of 8% even during the Covid-19 pandemic crisis.

Smart Recognition System for High Security Zone

Abstract: In today’s world almost all the big institutions face significant security issues; thus, they need a few uniquely prepared staff to satisfy the necessary security. These work force, as being human, commit errors which might influence the degree of safety. A proposed answer for the previously mentioned problem could likewise be a Face Recognition Security System, which can distinguish gate crashers to confined or high security regions and help in limiting human mistake. So far, we have studied the image comparison techniques and tested the same against our dataset of sample images. Our program can almost accurately separate two similar or dissimilar images. We have further tested our sample images against different backgrounds, angles, size etc. and observed the output. We have also done the facial recognition part, i.e., we are able to detect faces and match it with that face from our database and show the result. Finally, we have done iris recognition by comparing static images of iris which gives us an output by showing whether the iris matches or not. Also, in this report we have discussed about our future plan.

An Assessment of Liquidity and Shareholders’ Earnings of Listed Firms at The Nairobi Securities Exchange, Kenya

The global changes in the business environment and the increased demand for improved shareholder’s earnings have prompted big firms to re-examine their liquidity levels. During the 2008 global economic crisis, many big institutions experienced liquidity challenges which led to the decline in the earnings of shareholders. The current study was therefore necessary to analyse the effect of liquidity on shareholders earnings of listed firms at the Nairobi Securities Exchange. The liquidity theories, were used to guide the research. A descriptive research design was used in this study. The study’s target population was all listed companies on the Nairobi Securities Exchange over the period 2015 to 2021. The 64 companies were analyzed using the census study. Data had been collected using a secondary data collection sheet. The study employed secondary data obtained from the published financial statements of the respective firms, from the Nairobi Securities Exchange and the Capital Markets Data. A panel regression model was employed in the analysis of data with the aid of the stata version 14. The study found out that Liquidity had a positive significant effect on the shareholders earnings. The study recommends that listed firms should enhance its liquidity by investing more on liquid assets. This should entail more investments in treasury bills, treasury bonds and other liquid stocks. They should also diversify their investments by investing in money markets. Additionally it should enhance its liquidity by controlling its overheads through getting rid of unnecessary expenses. Secondly, the listed firms need to expand its asset base.

DLCP2F: a DL-based cryptocurrency price prediction framework

Cryptocurrencies are distributed digital currencies that have emerged as a consequence of financial technology advancement. In 2017, cryptocurrencies have shown a huge rise in their market capitalization and popularity. They are now employed in today’s financial systems as individual investors, corporate firms, and big institutions are heavily investing in them. However, this industry is less stable than traditional currency markets. It can be affected by several legal, sentimental, and technical factors, so it is highly volatile, dynamic, uncertain, and unpredictable, hence, accurate forecasting is essential. Recently, cryptocurrency price prediction becomes a trending research topic globally. Various machine and deep learning algorithms, e.g., Neural Networks (NN), Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), and Bidirectional LSTM (BiLSTM) were utilized to analyze the factors influencing the prices of the cryptocurrencies and accordingly predict them. This paper suggests a five-phase framework for cryptocurrency price prediction based on two state-of-the-art deep learning architectures (i.e., BiLSTM and GRU). The current study uses three public real-time cryptocurrency datasets from “Yahoo Finance”. Bidirectional Long Short-Term Memory and Gated Recurrent Unit deep learning-based algorithms are used to forecast the prices of three popular cryptocurrencies (i.e., Bitcoin, Ethereum, and Cardano). The Grid Search approach is used for the hyperparameters optimization processes. Results indicate that GRU outperformed the BiLSTM algorithm for Bitcoin, Ethereum, and Cardano, respectively. The lowest RMSE for the GRU model was found to be 0.01711, 0.02662, and 0.00852 for Bitcoin, Ethereum, and Cardano, respectively. Experimental results proved the significant performance of the proposed framework that achieves the minimum MSE and RMSE values.

Influences of inter- and intra-row spacing on the growth and head yield of cabbage (Brassica oleracea var. capitata) in western Amhara, Ethiopia

Abstract Plant population of 40,000 ha−1 with the respective inter- and intra-row spacing of 50 cm × 50 cm is the blanket recommendation for the production of head cabbage in Ethiopia. However, producers complain that this spacing produces too large head size, which is not the market's preference for household consumption instead for hotels and big institutions like universities. This two-season field experiment was conducted to optimize the head cabbage yield with appropriate head size by adjusting inter- and intra-row spacing. The result of the combined analysis over location and season revealed that all tested parameters were significantly (P < 0.05) influenced by the interaction effect of inter- and intra-row spacing. The combinations of 35 cm × 30 cm, 35 cm × 50 cm, and 50 cm × 30 cm inter- and intra-row spacing gave the highest head yield of 45, 43 significantly, and 42 t ha−1, respectively as compared to other treatment combinations. The interaction of the lowest inter- and intra-row spacing of 35 cm × 30 cm gave the lowest average head weight of 923 g of cabbage. The result showed that as intra-row spacing increased from 30 to 50 cm with all possible combinations of inter-row spacing, head-sized cabbage increased linearly. The current study identified that blanket recommendation of 50 cm × 50 cm inter-and intra-row spacing which assures a plant population of 40,000 ha−1 produced more than 1.4 kg individual head weight with a yield penalty of 10.70 t ha−1 compared to 50 cm × 30 cm inter- and intra-row spacing combination which assures a plant population of 66,667 ha−1. The current study confirmed that the earlier blanket recommendation of 40,000 plants ha−1 should be enhanced to a plant population of 66,667 ha−1 with a yield advantage of 131%. Concretely the manifested plant population difference gives an opportunity to producers to harvest a maximum yield with an acceptable head size of 1.2 kg. Therefore, it is concluded that the combination of 50 cm × 30 cm inter- and intra-row spacing assures that a plant population of 66,667 ha−1 is optimum for the production of head cabbage in the study and similar agro-ecologies.

The Catholic Church’s Responsibility in Creating a Safeguarding Culture

The safeguarding of minors and of vulnerable adult persons is an intrinsic aspect of the mission that the Lord has entrusted the Church and it is the responsibility of all the faithful to fulfil it, whatever capacity they hold in the Church. Unfortunately, it is not possible to eradicate child abuse entirely as it is a human reality, but much can be done by creating a culture of safe space and safe relationships within the Church and beyond. The Catholic Church, as the oldest and biggest institution in the world and with its religious and moral values, has a special responsibility in preventing any kind of abuse, in protecting the most vulnerable, and furthermore, in Safeguarding; in creating safe spaces and safe relationships. Listening to victims and survivors of abuse who have been harmed in the Church or outside, is key for being and acting in a responsible, accountable, and transparent way. This is the cornerstone for credibility and for promoting the faith.

HRM Practices develop product differentiation and cost leadership strategy, enabling Organizations to attain competitive advantage: A narrative review

Human resource management practice (HRMP) has been broadly acknowledged and widely recognized by almost every organization. Many studies have been conducted to review the application of human resource management (HRM) and other aspects that have manifested and been determined to be true in a variety of scenarios. HRM practices have been found to be essential and effective in the delivery of services and socioeconomic growth. In well-established organizations, up-to-the-level performance and competition are impossible without the required skilled, well-motivated people working in a good human resource management program development. In both small and big educational institutions, a framework that relies on human resources management strategies for program implementation is required in an educational setting the most essential practices of human resource management are selection and recruitment, appraisal of performance, training and development, and reward and rumination systems. It is very pertinent for an organization to comprehend methods of attracting, retaining boast the Morales of those in the marketplace who are skilled and competent. Organizations by the virtue of implementation of soft dimensions of HRM become able to gain a competitive edge. From the available literature it very evident that through the procedures and practices of human resource management not only the performances of an organization are enhanced but it becomes able to get what is called “competitive advantage”.

Analysis of Big Data Sharing Economy under Blockchain Technology

With the continuous development of big data technology, people have new development and pursuit in the fields of production, distribution, exchange, consumption and so on. During this period, the sharing economy came into being. The big data sharing economy refers to: relying on the support of big data, institutions or individuals with idle resources will pay others to use their own resources, and sharers create value by sharing their idle resources. With the support of blockchain technology, the big data sharing economy has been further developed, providing a new development idea and model for people's consumption. It has become a strong support for promoting the new development of the sharing economy and improving the business model of the sharing economy.

4 - Leadership Philosophy and Interventions to Support Middle-level Units within Large Academic Institutions: Experiences at the Makerere Peace and Conflict Studies Centre

This article discusses practical lessons on how leadership intervention philosophy can be used to design and ensure that an academic unit within a big institution realises its mandate. The interventions took place at the Peace and Conflict Studies Centre (MPCSC) at Makerere University between 2015 and 2019. The undertaking was guided by systemic leadership intervention philosophy and transformational leadership. The methods used in the intervention included: leadership interventions, secondary data analysis, narrative analysis and autoethnography. The article uses a combination of analytical and auto-biographical reporting styles. Major findings include the following: there is a leadership skilling gap between high-level and mid-level managers in large university units; in large academic institutions, mid-level managers must combine traits and process leadership approaches in order realise progress. Key observations: student enrolment drives achieved a slight improvement in numbers (from 14 % in 2015/2016 to 42 % in 2018/2019); a minor improvement in workstations led to a more than 100 per cent increment in usage by staff and students; the Centre noticed a 63 per cent completion rate of specialised skills training by staff; on average, interdisciplinary research teams perform better than single discipline teams, but the former required extra effort to keep together; the interventions led to a 70 per cent increase in community outreach through avenues such as projects, experiential learning sessions, consultancies, etc.

MemChar: Portable Low-Power and Low-Cost Characterization Tool for Memristor Devices

Recently, Memristor (MR) device has received much attention in many applications, including memory, computing, neuromorphic, sensing, and security. Electrical characterization and testing of MR are among the main challenges facing MR technology. Available MR characterization tools are costly and bulky, limiting the research contributions in this field to big institutions. Furthermore, there is a need for a portable testing platform that provides the means to extract MR parameters, mainly when used in sensing or security applications. This work proposes a novel power-efficient, cost-effective, lightweight, and automated Arduino-based MR characterization platform named MemChar. A detailed circuit and system implementation of MemChar are presented. MemChar functionality results are compared to industry-standard device parameter analyzer tools, i.e., Keithley 4200A, with excellent correlation. MemChar is an easy-to-implement and user-friendly platform that provides a significant milestone toward utilizing MR devices in mobile, IoT, and sensing applications.

Decentralized Nation: Solving the Web’s Identity Crisis

The web of today whether you prefer to call it web 2.0, web 3.0, web 5.0 or even the metaverse is at a critical stage of evolution and challenge, largely centered around its crisis of identity. Like teenagers who cannot assess properly their reason for being and do not seem ready to take responsibility for their actions, we are constantly blaming the very system we are trying to get away from. To truly realize the benefits from innovation and technology, this crisis has to be resolved, not just through tactical solutions but through developments that enhance the sustainability of the web and its benefits. Significant strides are being made in the evolution of digital services enabled by technology, regulation, and the sheer pace of societal change. The journey to the decentralized web is mirroring the convergence of the physical and digital worlds across all economies and is increasingly embracing the digital native world. Technology has provided the foundational platform for individuals and entities to create and manage wealth, potentially without the need for big institutions. Ironically, despite all of the advancements, we are still facing an unprecedented and increasing wealth gap. Clearly, the system is broken, not just around the edges but at the very core of the democratic underpinning of our society. In this whitepaper, we propose how artificial intelligence on blockchain can be used to generate a new class of identity through direct human computer interaction. We demonstrate how this, combined with new perspectives for sustaining community and governance embedded within the use of blockchain technology, will underpin a sustainable solution to protect identity, authorship and privacy at the same time while contributing to restore trust amongst members of a future decentralized nation and hence contribute to solving the web most significant identity crisis.

Privately Publishing Internet of Things Data: Bring Personalized Sampling Into Differentially Private Mechanisms

Massive Internet of Things (IoT) data sets are possessed by big institutions serving daily life because IoT devices are widely used in our daily life such as wearable devices and smart home devices. Publishing these data sets among various institutions causes an increasing number of users to concern their personal privacy. Differential privacy is the state-of-the-art concept of privacy preservation, but it suffers from the low accuracy. In this article, we improve differentially private mechanisms including the Laplace mechanism as well as the sample and aggregation mechanism by bringing the personalized sampling technology into these mechanisms so that IoT data sets can be privately published through differentially private mechanisms. In particular, improved mechanisms assign a personalized sampling probability to each data record in a way that their accuracy can be improved. We analyse improved mechanisms in terms of their privacy and accuracy. Then, we empirically demonstrate that the performance of improved mechanisms is better than original mechanisms through extensive experiments on synthetic data sets and real-world data sets.

CarFree: Hassle-Free Object Detection Dataset Generation Using Carla Autonomous Driving Simulator

For safe autonomous driving, deep neural network (DNN)-based perception systems play essential roles, where a vast amount of driving images should be manually collected and labeled with ground truth (GT) for training and validation purposes. After observing the manual GT generation’s high cost and unavoidable human errors, this study presents an open-source automatic GT generation tool, CarFree, based on the Carla autonomous driving simulator. By that, we aim to democratize the daunting task of (in particular) object detection dataset generation, which was only possible by big companies or institutes due to its high cost. CarFree comprises (i) a data extraction client that automatically collects relevant information from the Carla simulator’s server and (ii) a post-processing software that produces precise 2D bounding boxes of vehicles and pedestrians on the gathered driving images. Our evaluation results show that CarFree can generate a considerable amount of realistic driving images along with their GTs in a reasonable time. Moreover, using the synthesized training images with artificially made unusual weather and lighting conditions, which are difficult to obtain in real-world driving scenarios, CarFree significantly improves the object detection accuracy in the real world, particularly in the case of harsh environments. With CarFree, we expect its users to generate a variety of object detection datasets in hassle-free ways.

Deinstitutionalisation and ‘Home Turn’ Policies: Promoting or Hampering Social Inclusion?

By the end of the twentieth century, caring for vulnerable adults in the community had become a pervasive policy trend in the Western world. In this article, this policy is described in two phases: deinstitutionalisation and the ‘home turn’ that are reflected from the perspective of social inclusion. Deinstitutionalisation has meant large institutions and asylums being replaced by group homes and communal‐supported housing units in the community. In the second and current phase, the ‘home turn’ emphasises well‐developed community care, home‐based services, everyone’s right to have their own home, and having a valued place in the community. In this semi‐systematic narrative review, the widely shared incentives, premises, and criticisms of deinstitutionalisation and the ‘home turn’ are mapped from the research literature. The special focus is on the possibilities of and hindrances to social inclusion in both policy phases. The research results are mixed and conflicting concerning social inclusion, but there exists a wide consensus that small housing units and supported housing with devoted workers enhance social inclusion better than big institutions. However, the prevalent view is that deinstitutionalisation has not fulfilled its promise of social inclusion, and although the ‘home turn’ is a step in the right direction, there are still problems in strengthening service users’ involvement and creating inclusive and accepting communities.