An Economic Theory of Academic Engagement Norms: The Struggle for Popularity and Normative Hegemony in Secondary Schools

[Excerpt] Why and how do groups create norms? Kenneth Arrow proposed that “norms of social behavior, including ethical and moral codes, ….are reactions of society to compensate for market failure”. This internalize the real externalities explanation for norms is also standard among rational choice theorists in sociology. The situation becomes more complex when we recognize some actions create positive externalities for some individuals and negative externalities for others. Often this results in no norm being established. However, sometimes one segment of a social system has normative hegemony and enforces norms that enhance their power and prestige at the expense of other groups. Norms regarding caste in India, for example, were functional for Brahmins but humiliating for Harijans. Caste and status norms of this type will also be referred to as “Honor us; Not them” norms. Such norms arise when one group is much more powerful (has greater ability to enforce their preferred social norm) than other groups and it imposes its will on others. An additional requirement is that the people who oppose the norm established by the dominant group must be unable or unwilling to leave the social system in which the norm operates

Peer Harassment: A Weapon in the Struggle for Popularity and Normative Hegemony in American Secondary Schools

This paper addresses two of secondary education’s most serious problems—peer abuse of weaker socially unskilled students and a peer culture that in most schools discourages many students from trying to be all that they can be academically. We have documented the two problems by reviewing ethnographies of secondary schools, by interviewing students in eight suburban high schools and by analyzing data from questionnaires completed by nearly 100,000 students at Educational Excellence Alliance schools. Grounded in these observations, we built a simple mathematical model of peer harassment and popularity and of the pressures for conformity that are created by the struggle for popularity and then tested it in data from the Educational Excellence Alliance. Students entering middle school learn its norms by trying to copy the traits and behaviors of students who are respected and by avoiding contact with those who are frequently harassed. Peer norms are enforced by encouraging ‘wannabes,’ aspirants for admission to popular crowds, to harass those who visibly violate them. Consequently, one can infer the norms by noting who gets harassed and who doesn’t. Traits that in EEA data led to higher risks of being bullied and harassed were: being in a special education, being in gifted programs, taking accelerated courses in middle school, tutoring other students, enjoying school assignments, taking a theatre course, not liking rap-hip hop music and liking instead musicals, heavy metal, country, or classical music. The relationship between harassment and academic effort was curvilinear; both the nerds and the slackers were harassed. To some degree these norms are, as Kenneth Arrow suggests, trying to internalize externalities. But why are music preferences such good predictors of harassment? Why are the student tutors victimized? We propose that norms also have a “We’re cool, Honor us” function of legitimating the high status that the leading crowds claim for themselves. As a result the traits and interests that members of leading crowds have in common tend to become normative for everyone. The norms that prevailed were: “Spend your time socializing, do not “study too hard.” Value classmates for their athletic prowess and their attractiveness, not their interest in history or their accomplishments in science.

Neural Networks

We present an overview of current research on artificial neural networks, emphasizing a statistical perspective. We view neural networks as parameterized graphs that make probabilistic assumptions about data, and view learning algorithms as methods for finding parameter values that look probable in the light of the data. We discuss basic issues in representation and learning, and treat some of the practical issues that arise in fitting networks to data. We also discuss links between neural networks and the general formalism of graphical models

VALIDATING CONTINGENT VALUATION WITH SURVEYS OF EXPERTS

Contingent-valuation estimates for white-water boating passengers are compared with Likert ratings by river guides. The approach involves asking whether passengers and their guides ordinally rank alternative flows the same. The National Oceanic and Atmospheric Administration's Contingent Valuation Panel (1993) suggested "one might want to compare its (contingent-valuation's) outcome with that provided by a panel of experts." River guides constitute a counterfactual panel of "experts." For commercial trips, optimum flows are 34,000 cfs and 31,000 cfs for passengers and guides, and the comparable figures for private trips are 28,000 cfs and 29,000 cfs. In the NOAA Panel framework, passengers can evaluate the consequences of various river flows and translate this into contingent-valuation responses.Resource /Energy Economics and Policy,

A hierarchical latent variable model for data visualization

Visualization has proven to be a powerful and widely-applicable tool the analysis and interpretation of data. Most visualization algorithms aim to find a projection from the data space down to a two-dimensional visualization space. However, for complex data sets living in a high-dimensional space it is unlikely that a single two-dimensional projection can reveal all of the interesting structure. We therefore introduce a hierarchical visualization algorithm which allows the complete data set to be visualized at the top level, with clusters and sub-clusters of data points visualized at deeper levels. The algorithm is based on a hierarchical mixture of latent variable models, whose parameters are estimated using the expectation-maximization algorithm. We demonstrate the principle of the approach first on a toy data set, and then apply the algorithm to the visualization of a synthetic data set in 12 dimensions obtained from a simulation of multi-phase flows in oil pipelines and to data in 36 dimensions derived from satellite images

Probabilistic principal component analysis

Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined through maximum-likelihood estimation of parameters in a latent variable model closely related to factor analysis. We consider the properties of the associated likelihood function, giving an EM algorithm for estimating the principal subspace iteratively, and discuss the advantages conveyed by the definition of a probability density function for PCA

All-sky Measurements of Short Period Waves Imaged in the OI (557.7 nm), Na(589.2 nm) and Near Infrared OH and O2(0,1) Nightglow Emissions During the ALOHA-93 Campaign

As part of the ALOHA‐93 campaign a high performance all‐sky CCD imaging system was operated at Haleakala Crater, Maui, to obtain novel information on the properties and sources of short period gravity waves over an extended height range ∼80–100 km. Sequential observations of the near infrared OH and O2(0,1) bands and the visible wavelength OI(557.7 nm) and Na(589.2 nm) line emissions have enabled a unique comparison of the morphology and dynamics of the wave motions and their occurrence frequency at each emission altitude to be made. Two major findings are: (a) the detection of significantly higher amounts of wave structure at OI altitudes (∼96 km) compared with that in the OH emission (∼87 km) and (b) the discovery of an unusual morphology, small‐scale wave pattern that was most conspicuous in the OI emission and essentially absent at OH heights. These data provide strong evidence for the presence of ducted wave motions in the lower thermosphere

Tempo and intensity of pre-task music modulate neural activity during reactive task performance

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2013 The Authors.Research has shown that not only do young athletes purposively use music to manage their emotional state (Bishop, Karageorghis, & Loizou, 2007), but also that brief periods of music listening may facilitate their subsequent reactive performance (Bishop, Karageorghis, & Kinrade, 2009). We report an fMRI study in which young athletes lay in an MRI scanner and listened to a popular music track immediately prior to performance of a three-choice reaction time task; intensity and tempo were modified such that six excerpts (2 intensities × 3 tempi) were created. Neural activity was measured throughout. Faster tempi and higher intensity collectively yielded activation in structures integral to visual perception (inferior temporal gyrus), allocation of attention (cuneus, inferior parietal lobule, supramarginal gyrus), and motor control (putamen), during reactive performance. The implications for music listening as a pre-competition strategy in sport are discussed

Intimal smooth muscle cells are a source but not a sensor of anti-inflammatory CYP450 derived oxylipins

AbstractVascular pathologies are associated with changes in the presence and expression of morphologically distinct vascular smooth muscle cells. In particular, in complex human vascular lesions and models of disease in pigs and rodents, an intimal smooth muscle cell (iSMC) which exhibits a stable epithelioid or rhomboid phenotype in culture is often found to be present in high numbers, and may represent the reemergence of a distinct developmental vascular smooth muscle cell phenotype. The CYP450-oxylipin - soluble epoxide hydrolase (sEH) pathway is currently of great interest in targeting for cardiovascular disease. sEH inhibitors limit the development of hypertension, diabetes, atherosclerosis and aneurysm formation in animal models. We have investigated the expression of CYP450-oxylipin-sEH pathway enzymes and their metabolites in paired intimal (iSMC) and medial (mSMC) cells isolated from rat aorta. iSMC basally released significantly larger amounts of epoxy-oxylipin CYP450 products from eicosapentaenoic acid > docosahexaenoic acid > arachidonic acid > linoleic acid, and expressed higher levels of CYP2C12, CYP2B1, but not CYP2J mRNA compared to mSMC. When stimulated with the pro-inflammatory TLR4 ligand LPS, epoxy-oxylipin production did not change greatly in iSMC. In contrast, LPS induced epoxy-oxylipin products in mSMC and induced CYP2J4. iSMC and mSMC express sEH which metabolizes primary epoxy-oxylipins to their dihydroxy-counterparts. The sEH inhibitors TPPU or AUDA inhibited LPS-induced NFκB activation and iNOS induction in mSMC, but had no effect on NFκB nuclear localization or inducible nitric oxide synthase in iSMC; effects which were recapitulated in part by addition of authentic epoxy-oxylipins. iSMCs are a rich source but not a sensor of anti-inflammatory epoxy-oxylipins. Complex lesions that contain high levels of iSMCs may be more resistant to the protective effects of sEH inhibitors