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The purpose of this paper is to study the viability of implementing a protocol-guided model designed to provide structure and focus for teacher collaboration from Shanghai in today’s US public schools. The authors examine whether the new model, Teacher Peer Excellence Group (TPEG), fosters the desired key features of productive communities of practice where teachers can jointly construct, transform, preserve, and continuously deepen the meaning of effective teaching. The authors also explore the extent to which existing school conditions – principal instructional leadership, trust, teacher efficacy, and teachers’ sense of school-wide professional community – enable or moderate the desired outcomes.

Data for this paper are drawn from a series of surveys administered to teachers from 24 pilot schools in six school districts over two school years. Descriptive and multilevel modeling analyses are conducted.

The findings provide encouraging evidence that, given sufficient support and guidance, teachers report higher levels of engagement in deprivatized practice and instructional collaboration. These findings also hold after controlling for key enabling conditions and school characteristics.

The TPEG approach challenges school leaders to take on the responsibilities of helping teachers make their practice public, sharable, and better – three critical objectives in the shift to develop the profession of teaching.

The indication of TPEG model’s positive impact on strengthening the features of communities of practice in selected public schools provides the impetus for further efforts in understanding the transformational changes needed and challenges ahead at the classroom, school, and district levels.

The purpose of this paper is to examine the relative financial strength and endurance of several paired classes of farmers according to business maturity (beginning versus mature farm businesses), farm operators’ age/experience (young versus older, more experienced farm operators), and farm size (small vs large farm businesses) by utilizing random-effects ordered logistic techniques.

This study uses a credit migration approach to analyze the factors that impact the probability of farm credit migration rates. An ordered logit model is used to assess the influence that factors have on a farm upgrading, staying same, or downgrading in credit rating.

Results show that increasing farm size will lead to a higher probability of class upgrades. Being a young farm operator, meanwhile, decreases this probability. Positive changes in money supply and farm real estate values were found to increase the likelihood of credit upgrades. Results also show trend reversal of credit risk movement, where upgrades (downgrades) are more likely to be followed by downgrades (upgrades).

With farms being dependent on capital for growth, knowing what factors affect the ability of a farm to obtain credit lends insight in the agricultural credit markets. This paper is also the first to assess the impacts of these factors on small farms which constitute 92 percent of farms in the USA per the US Department of Agriculture.