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The paper discusses a partnership between Huston–Tillotson University (HT), a Historically Black College and University (HBCU) and the Austin Independent School District (AISD), a minority-serving school district, both in Austin, Texas, with a grant provided by Apple Inc. (Apple). The purpose of the partnerships is that valuable relationships can increase the number of African American male teachers in primary and secondary education in minority-serving public schools. The African American Male Teacher Initiative (AAMTI) at HT was created as an innovative approach to recruit and select 20 African American males each year of a four-year grant provided by Apple.

This paper reviewed the literature on the lack and need for African American male public school teachers. Once the data is established during a three-to-four-year period, a mixed-method approach will be utilized to examine data retrieved from interviews, surveys, demographics of student participants, numerical data and retention and graduation rates. This will establish whether strategic partnerships can successfully increase the number of qualified African American males in public education.

This paper proposes and provides research evidence that African American male teachers can positively impact all students in the classroom setting.

There is limited data to test a hypothesis on the effectiveness of a partnership between the university and public school to increase the number of African American male teachers through recruitment – selection and retention efforts. Therefore, follow-up research is needed for the first graduating class of 2024.

The broader impact of this paper is to show that partnerships between universities and public schools with corporate sponsorship can positively increase the number of African American male teachers prepared to teach in public schools through strategic recruitment and selection efforts.

This paper can serve as a model for universities and school districts to implement. High placement of prepared Black male teachers in public schools can reduce the school-to-prison pipeline and juvenile homicides and defeat generational poverty.

Much research highlights the problems associated with a lack of African American male teachers. This paper includes the challenges but offers a sound basis for practical solutions.

The purpose of this article is to examine the expectations, challenges and tensions officers describe while engaged with public schools to demonstrate that officers engage with students in public schools in a conscious, goal-oriented process to establish and maintain useful relationships.

Data collection involved 104 semi-structured interviews (including follow up interviews) and 31 focus groups, conducted between 2014 and 2018 with police officers working in rural areas of a province in Atlantic Canada.

Utilizing the concept of social capital, we analyze practices of investments alongside the understanding of rurality as socially interconnected and the rural school as a particular site of interconnectedness for police officers. We demonstrate how, while accumulating social capital, officers face role tension and fundamental barriers when trying to integrate into rural school communities.

By demonstrating the specificities of building social capital in schools and community environments in a rural setting, we contribute to understandings regarding the unique opportunities and challenges faced by police in rural schools in integrating effectively into schools and responding to youth-specific problems.

This study aims to present radical abolition studies, which encourages us to (re)member that the abolition of institutions and systems is incomplete without the abolition of their attendant epistemes of domination. The authors draw on the etymology of the word radical to encourage abolitionist praxis to grab systemic harm at its epistemological roots. Within radical abolition studies, this study presents Black abolition theory, which aims to make explicit a theorization of Blackness and works to abolish the episteme of anti-Blackness.

This paper offers Black abolition theory within radical abolition studies to reground abolition in its Black theoretical roots and to interrogate the concept of anti-Blackness and other epistemes of domination in abolitionist study and practice. Using a close reading of W.E.B. Du Bois’ Black Reconstruction, and subsequent books and articles in abolition studies and educational studies that reference it, the authors highlight Du Bois’ original conceptualization of abolitionism as an ultimate refutation of a racial-social order and anti-Blackness. The authors then put Michael Dumas and kihana ross’ theory of BlackCrit into conversation with abolitionist and educational theory to push forward Black abolition theory.

Radical abolition studies and its attendant strand of Black abolition theory presented in this paper encourages scholars and practitioners to go beyond the dismantling of current instantiations of systemic harm for Black and other minoritized people – such as the school as it currently operates – and encourages the questioning and dismantling of the epistemes of domination sitting at the foundation of these systems of harm.

Black abolition theory contextualizes abolition in education by rooting abolitionist educational praxis in Black lineages. More generally, radical abolition studies encourages further research, study and collaboration in partnership with others who have historically participated in the fight against being labeled as subhuman to upend all epistemes of domination.

This paper aims to provide a historical overview of AA, its purpose and benefits, the legal rationale for the SCOTUS ruling and what it means for colleges and the workplace regarding equitable opportunities for minority groups (which include women, Blacks, Hispanics, Asians and other low-income populations), as they aim for the “American dream”.

SCOTUS decision and rationale, along with literature.

The race-based affirmative action (AA) precedent was recently overturned by the Supreme Court of the United States (SCOTUS) in the case of Students for Fair Admission (SFFA), Inc. vs President and Fellows of Harvard College/University of North Carolina. SCOTUS ruled that race cannot be a specific basis for college admission. In other words, public and private colleges and universities will no longer be able to consider “race” as a factor in deciding which qualified applicants should be admitted to enhance the diversity of their student body.

This is an original analysis.

This study explores a hegemonic alliance and the role of relational forms of accounting and accountablity in the making of contemporary capitalism.

We use the WikiLeaks “Cablegate” documents to provide an account of the detailed machinations between interest groups (corporations and the state) that are constitutive of hegemonic activity.

Our analysis of the “Cablegate” documents shows that the US and Chevron were crafting a central role for Turkmenistan and its president on the global political stage as early as 2007, despite offical reporting beginning only in 2009. The documents exemplify how “accountability gaps” occlude the understanding of interdependence between capital and the state.

The study contributes to a growing idea that official accounts offer a fictionalized narrative of corporations as existing independently, and thus expands the boundaries associated with studying multinational corporate activities to include their interdependencies with the modern state.

The study traces how global capitalism extends into new territories through diplomatic channels, as a strategic initiative between powerful state and capital interests, arguing that the outcome is the empowerment of authoritarian states at the cost of democracy.

The study argues that previous accounting and accountability research has overlooked the larger picture of how capital and the state work together to secure a mutual hegemonic interest. We advocate for a more complete account of these activities that circumvents official, often restricted, views of global capitalism.

Earned value management (EVM)–based models for estimating project actual duration (AD) and cost at completion using various methods are continuously developed to improve the accuracy and actualization of predicted values. This study primarily aimed to examine natural gradient boosting (NGBoost-2020) with the classification and regression trees (CART) base model (base learner). To the best of the authors' knowledge, this concept has never been applied to EVM AD forecasting problem. Consequently, the authors compared this method to the single K-nearest neighbor (KNN) method, the ensemble method of extreme gradient boosting (XGBoost-2016) with the CART base model and the optimal equation of EVM, the earned schedule (ES) equation with the performance factor equal to 1 (ES1). The paper also sought to determine the extent to which the World Bank's two legal factors affect countries and how the two legal causes of delay (related to institutional flaws) influence AD prediction models.

In this paper, data from 30 construction projects of various building types in Iran, Pakistan, India, Turkey, Malaysia and Nigeria (due to the high number of delayed projects and the detrimental effects of these delays in these countries) were used to develop three models. The target variable of the models was a dimensionless output, the ratio of estimated duration to completion (ETC(t)) to planned duration (PD). Furthermore, 426 tracking periods were used to build the three models, with 353 samples and 23 projects in the training set, 73 patterns (17% of the total) and six projects (21% of the total) in the testing set. Furthermore, 17 dimensionless input variables were used, including ten variables based on the main variables and performance indices of EVM and several other variables detailed in the study. The three models were subsequently created using Python and several GitHub-hosted codes.

For the testing set of the optimal model (NGBoost), the better percentage mean (better%) of the prediction error (based on projects with a lower error percentage) of the NGBoost compared to two KNN and ES1 single models, as well as the total mean absolute percentage error (MAPE) and mean lags (MeLa) (indicating model stability) were 100, 83.33, 5.62 and 3.17%, respectively. Notably, the total MAPE and MeLa for the NGBoost model testing set, which had ten EVM-based input variables, were 6.74 and 5.20%, respectively. The ensemble artificial intelligence (AI) models exhibited a much lower MAPE than ES1. Additionally, ES1 was less stable in prediction than NGBoost. The possibility of excessive and unusual MAPE and MeLa values occurred only in the two single models. However, on some data sets, ES1 outperformed AI models. NGBoost also outperformed other models, especially single models for most developing countries, and was more accurate than previously presented optimized models. In addition, sensitivity analysis was conducted on the NGBoost predicted outputs of 30 projects using the SHapley Additive exPlanations (SHAP) method. All variables demonstrated an effect on ETC(t)/PD. The results revealed that the most influential input variables in order of importance were actual time (AT) to PD, regulatory quality (RQ), earned duration (ED) to PD, schedule cost index (SCI), planned complete percentage, rule of law (RL), actual complete percentage (ACP) and ETC(t) of the ES optimal equation to PD. The probabilistic hybrid model was selected based on the outputs predicted by the NGBoost and XGBoost models and the MAPE values from three AI models. The 95% prediction interval of the NGBoost–XGBoost model revealed that 96.10 and 98.60% of the actual output values of the testing and training sets are within this interval, respectively.

Due to the use of projects performed in different countries, it was not possible to distribute the questionnaire to the managers and stakeholders of 30 projects in six developing countries. Due to the low number of EVM-based projects in various references, it was unfeasible to utilize other types of projects. Future prospects include evaluating the accuracy and stability of NGBoost for timely and non-fluctuating projects (mostly in developed countries), considering a greater number of legal/institutional variables as input, using legal/institutional/internal/inflation inputs for complex projects with extremely high uncertainty (such as bridge and road construction) and integrating these inputs and NGBoost with new technologies (such as blockchain, radio frequency identification (RFID) systems, building information modeling (BIM) and Internet of things (IoT)).

The legal/intuitive recommendations made to governments are strict control of prices, adequate supervision, removal of additional rules, removal of unfair regulations, clarification of the future trend of a law change, strict monitoring of property rights, simplification of the processes for obtaining permits and elimination of unnecessary changes particularly in developing countries and at the onset of irregular projects with limited information and numerous uncertainties. Furthermore, the managers and stakeholders of this group of projects were informed of the significance of seven construction variables (institutional/legal external risks, internal factors and inflation) at an early stage, using time series (dynamic) models to predict AD, accurate calculation of progress percentage variables, the effectiveness of building type in non-residential projects, regular updating inflation during implementation, effectiveness of employer type in the early stage of public projects in addition to the late stage of private projects, and allocating reserve duration (buffer) in order to respond to institutional/legal risks.

Ensemble methods were optimized in 70% of references. To the authors' knowledge, NGBoost from the set of ensemble methods was not used to estimate construction project duration and delays. NGBoost is an effective method for considering uncertainties in irregular projects and is often implemented in developing countries. Furthermore, AD estimation models do fail to incorporate RQ and RL from the World Bank's worldwide governance indicators (WGI) as risk-based inputs. In addition, the various WGI, EVM and inflation variables are not combined with substantial degrees of delay institutional risks as inputs. Consequently, due to the existence of critical and complex risks in different countries, it is vital to consider legal and institutional factors. This is especially recommended if an in-depth, accurate and reality-based method like SHAP is used for analysis.