A Shrinking Slice of the Pie: The Labour Income Share in Australia

The ‘wages breakout’ has been a recurring theme in the Australian public policy debate in recent years. Political conservatives, media commentators and some business groups have warned that Australian wages growth is unsustainable, or threatens to become unsustainable. This paper critically examines such claims and finds that they are not supported by the evidence. This paper shows that Australia has experienced the opposite of a ‘wages breakout’ since 2000. Over this period Australian real wages have not kept pace with productivity growth. This means that labour’s share of total income has fallen and capital’s share has risen. This paper also shows that many other OECD countries have experienced a falling labour share in recent years, but the fall in Australia’s labour share has been relatively large. The fall in the Australian labour share has been broadly-based – the labour share has fallen within a broad range of industries. Only a small portion of the fall can be ascribed to structural change in the economy towards low-labour share industries such as mining

Tidal Variation in Nitrogen Cycling in Oregon Sponges

As filter feeders, marine sponges are closely integrated with their environment. Sponges also host many diverse species of bacteria that carry out a gamut of metabolic processes, including several nitrogen transformations. The variable nature of tidal exchanges can influence the biogeochemicals available for the sponge and its associated microbes to obtain from the environment. As ambient nutrient concentrations change, it is suggested that the pumping rates of the sponge will change, thus altering the activity of the symbionts. To explore these hypotheses, ambient and exhalent water samples were collected at both high tide and low tide in Netarts Bay, Oregon. To assess pumping rates, transect images between tides were analyzed for changes in oscula diameter within species. Nitrate, ammonia, and total nitrogen concentrations were analyzed via spectroscopy. Transect results demonstrated decreased oscula diameter and therefore decreased pumping rates during high tide and inverse results at low tide. Significant variation was found between inhalant and exhalent nitrate, ammonia, and total nitrogen values between species and between tides. This suggests that ambient nitrogen concentrations influence internal nitrogen cycling, but varies between species. These results suggest that sponges and their associated microbial communities adjust their metabolism based on tidal influences

Marine Sponges as Bioindicators of Nitrogen within Estuaries on the Oregon Coast

As filter feeders, sponges are highly integrated with their environment. Many sponges also host diverse communities of bacteria, including many that are hypothesized to carry out a variety of nitrogen transformations. The presence of these bacteria makes sponges an integral part of the nitrogen cycle in their habitats and suggests that sponges are an excellent bioindicator of environmental conditions. To test these hypotheses, we collected sponge tissue from two Oregon estuaries and extracted microbial DNA from these samples. To assess bacterial diversity, we performed Denaturing Gradient Gel Electrophoresis (DGGE) on a fragment of the 16S gene. We also examined nitrogen cycling in sponges by examining the sponge samples for the presence of the amoA and nirS genes, which encode for enzymes in the nitrification and denitrification pathways, respectively. DGGE results showed diverse bacterial communities, with clear differences between the sites. The results also showed little variation within sites, but were suggestive of seasonal variation. Both functional genes were present in all five species of sponge that we collected. These results suggest that sponges and their associated bacterial communities play a critical role in nitrogen transformations within these bays and that these sponge-associated bacterial communities are bioindicators of environmental variation

Assessment of Canine Pancreas-Specific Lipase and Outcomes in Dogs with Hemodialysis-Dependent Acute Kidney Injury.

BackgroundRenal replacement therapies can be life-saving for dogs with severe acute kidney injury (AKI), however, comorbidities including pancreatitis might affect outcome.Hypothesis/objectivesTo investigate the prevalence of pancreas-specific lipase (Spec cPL) measurements consistent with pancreatitis (≥400 μg/L) in dogs undergoing intermittent hemodialysis (IHD) for treatment of AKI and to determine whether there were associations between 30-days outcomes and Spec cPL measurements.AnimalsFifty-three client-owned dogs presented to teaching hospitals between November 2008 and September 2016 that underwent IHD.MethodsRetrospective medical record review from dogs that received IHD for management of AKI and also had a Spec cPL measurement. Association between survival, dialysis-dependency, and Spec cPL measurements was assessed.ResultsForty of 53 (76%) dogs were alive at 30-days and 33/53(62%) had a Spec cPL result ≥400 μg/L. Spec cPL was not significantly different either between surviving (635.5 μg/L, range 29-1,001) and nonsurviving dogs (860 μg/L, range 56-1,001; P = 0.75) or between dialysis-dependent (1,001 μg/L, range 177-1,001) and nondialysis-dependent dogs (520 μg/L, range 29-1,001; P = 0.08). Spec cPL ≥400 μg/L was not significantly associated either with survival (P = 0.74) or dialysis-dependency (P = 0.33).Conclusions and clinical importanceResults revealed a high prevalence of Spec cPL ≥400 μg/L in dogs with AKI treated with IHD. No significant associations between Spec cPL and survival or dialysis-dependency in dogs with AKI at 30 days were identified in the current study, however, the latter could be due to lack of power in this study

The Influence of Intuitive Thinking Styles Versus Analytical Thinking Styles on the Use of Stereotypes in Judgments

Participants were randomly assigned to receive one of two instruction sets, one which encouraged them to rely on their intuitions and another which encouraged a more analytical thinking style. Participants were also randomly assigned to read one of two reports in order to decide whether an elementary school student who exhibited some ambiguously aggressive behaviors should be recommended for a program designed for children with behavioral problems. The otherwise identical reports were either concerning a student named “Eric” or a student named “Tyrone.” I predicted that participants would be more likely overall to recommend Tyrone for the behavioral program than Eric, but that this effect will be more pronounced for participants in the condition that encouraged an intuitive thinking style. This hypothesis was not confirmed. Participants in the condition that encouraged an intuitive thinking style were more confident in their judgments and less ambivalent about their judgments than participants who were encouraged to use an analytical thinking style.No embarg

Bias and Productivity in Humans and Machines

Where should better learning technology (such as machine learning or AI) improve decisions? I develop a model of decision-making in which better learning technology is complementary with experimentation. Noisy, inconsistent decision-making introduces quasi-experimental variation into training datasets, which complements learning. The model makes heterogeneous predictions about when machine learning algorithms can improve human biases. These algorithms can remove human biases exhibited in historical training data, but only if the human training decisions are sufficiently noisy; otherwise, the algorithms will codify or exacerbate existing biases. Algorithms need only a small amount of noise to correct biases that cause large productivity distortions. As the amount of noise increases, the machine learning can correct both large and increasingly small productivity distortions. The theoretical conditions necessary to completely eliminate bias are extreme and unlikely to appear in real datasets. The model provides theoretical microfoundations for why learning from biased historical datasets may lead to a decrease (if not a full elimination) of bias, as has been documented in several empirical settings. The model makes heterogeneous predictions about the use of human expertise in machine learning. Expert-labeled training datasets may be suboptimal if experts are insufficiently noisy, as prior research suggests. I discuss implications for regulation, labor markets, and business strategy

End of a Phase

If you had asked (as you did not) What I felt, I could have replied only with what has been heard before, For all that I imagined has been imagined before..

A Study of the Character of the Administrative Practices and Standards of Ten Small School Systems

The main purpose of this survey was to determine the character of the administrative relationships which exist in small school systems. This involved the study of five factors, namely, (1) The responsibilities of the superintendent as delegated by the board, (2) The responsibilities assumed by the board of education, (3) The relationship of the board of education to the staff, and (5) The relationship of the superintendent to the public