Catastrophic Error Research Articles

Landau vs Einstein: mathematics represents the universe

The modern theory of gravity is the Einstein space theory, which is described by mathematical methods of tensor analysis of Riemannian geometry. Einstein built on this basis one of the most successful and amazing theories. Complexity theories often lead to the extraction of foundations and, as is customary in theory, to obtaining meaningless results. Now the entire intellectual power of numerous researchers is directed at alternative theories, often based on erroneous ideas about Einstein's theory. An example of this is the catastrophic error in the definition of the coordinate transformation in the top manual on theoretical physics by L. D. Landau and E. M. Lifshitz.

Decorate the Newcomers: Visual Domain Prompt for Continual Test Time Adaptation

Continual Test-Time Adaptation (CTTA) aims to adapt the source model to continually changing unlabeled target domains without access to the source data. Existing methods mainly focus on model-based adaptation in a self-training manner, such as predicting pseudo labels for new domain datasets. Since pseudo labels are noisy and unreliable, these methods suffer from catastrophic forgetting and error accumulation when dealing with dynamic data distributions. Motivated by the prompt learning in NLP, in this paper, we propose to learn an image-layer visual domain prompt for target domains while having the source model parameters frozen. During testing, the changing target datasets can be adapted to the source model by reformulating the input data with the learned visual prompts. Specifically, we devise two types of prompts, i.e., domains-specific prompts and domains-agnostic prompts, to extract current domain knowledge and maintain the domain-shared knowledge in the continual adaptation. Furthermore, we design a homeostasis-based adaptation strategy to suppress domain-sensitive parameters in domain-invariant prompts to learn domain-shared knowledge more effectively. This transition from the model-dependent paradigm to the model-free one enables us to bypass the catastrophic forgetting and error accumulation problems. Experiments show that our proposed method achieves significant performance gains over state-of-the-art methods on four widely-used benchmarks, including CIFAR-10C, CIFAR-100C, ImageNet-C, and VLCS datasets.

Tranexamic acid at cesarean delivery: Drug-error deaths.

The use of tranexamic acid for postpartum hemorrhage has entered obstetrical practice globally with the evidence-based expectation of saving lives. This improvement in the care of women with postpartum hemorrhage has come at a price. For the anesthetist, having tranexamic acid ampoules close at hand would seem an obvious strategy to facilitate its use during cesarean delivery, an important setting for severe hemorrhage. Tragically, we have identified a number of recent instances of inadvertent intrathecal administration of tranexamic acid instead of local anesthetic for spinal anesthesia. Reported cases of this catastrophic error seem to be increasing. The profound neurotoxicity of tranexamic acid causes rapid-onset convulsions, with mortality of 50%. How can these tragic errors be averted? Drug safety alerts have been issued by the US Food and Drug Administration and the World Health Organization, but that is not enough. We recommend extensive dissemination of information to raise awareness of this potential hazard, and local hospital protocols to ensure that tranexamic acid is stored separately from anesthetic drugs, preferably outside the operating room and with an auxiliary warning label. Implementation of safety strategies on a very large scale will be needed to ensure that the life-saving potential of tranexamic acid is not eclipsed by drug-error mortality.

Tranexamic acid at cesarean delivery: drug-error deaths.

The use of tranexamic acid for postpartum hemorrhage has entered obstetrical practice globally with the evidence-based expectation of saving lives. This improvement in the care of women with postpartum hemorrhage has come at a price. For the anesthetist, having tranexamic acid ampoules close at hand would seem an obvious strategy to facilitate its use during cesarean delivery, an important setting for severe hemorrhage. Tragically, we have identified a number of recent instances of inadvertent intrathecal administration of tranexamic acid instead of local anesthetic for spinal anesthesia. Reported cases of this catastrophic error seem to be increasing. The profound neurotoxicity of tranexamic acid causes rapid-onset convulsions, with mortality of 50%. How can these tragic errors be averted? Drug safety alerts have been issued by the US Food and Drug Administration and the World Health Organization, but that is not enough. We recommend extensive dissemination of information to raise awareness of this potential hazard, and local hospital protocols to ensure that tranexamic acid is stored separately from anesthetic drugs, preferably outside the operating room and with an auxiliary warning label. Implementation of safety strategies on a very large scale will be needed to ensure that the life-saving potential of tranexamic acid is not eclipsed by drug-error mortality.

Tranexamic acid at cesarean delivery: drug-error deaths

The use of tranexamic acid for postpartum hemorrhage has entered obstetrical practice globally with the evidence-based expectation of saving lives. This improvement in the care of women with postpartum hemorrhage has come at a price. For the anesthetist, having tranexamic acid ampoules close at hand would seem an obvious strategy to facilitate its use during cesarean delivery, an important setting for severe hemorrhage. Tragically, we have identified a number of recent instances of inadvertent intrathecal administration of tranexamic acid instead of local anesthetic for spinal anesthesia. Reported cases of this catastrophic error seem to be increasing. The profound neurotoxicity of tranexamic acid causes rapid-onset convulsions, with mortality of 50%. How can these tragic errors be averted? Drug safety alerts have been issued by the US Food and Drug Administration and the World Health Organization, but that is not enough. We recommend extensive dissemination of information to raise awareness of this potential hazard, and local hospital protocols to ensure that tranexamic acid is stored separately from anesthetic drugs, preferably outside the operating room and with an auxiliary warning label. Implementation of safety strategies on a very large scale will be needed to ensure that the life-saving potential of tranexamic acid is not eclipsed by drug-error mortality.

Tranexamic acid at cesarean delivery: drug-error deaths

The use of tranexamic acid for postpartum hemorrhage has entered obstetrical practice globally with the evidence-based expectation of saving lives. This improvement in the care of women with postpartum hemorrhage has come at a price. For the anesthetist, having tranexamic acid ampoules close at hand would seem an obvious strategy to facilitate its use during cesarean delivery, an important setting for severe hemorrhage. Tragically, we have identified a number of recent instances of inadvertent intrathecal administration of tranexamic acid instead of local anesthetic for spinal anesthesia. Reported cases of this catastrophic error seem to be increasing. The profound neurotoxicity of tranexamic acid causes rapid-onset convulsions, with mortality of 50%.How can these tragic errors be averted? Drug safety alerts have been issued by the US Food and Drug Administration and the World Health Organization, but that is not enough. We recommend extensive dissemination of information to raise awareness of this potential hazard, and local hospital protocols to ensure that tranexamic acid is stored separately from anesthetic drugs, preferably outside the operating room and with an auxiliary warning label. Implementation of safety strategies on a very large scale will be needed to ensure that the life-saving potential of tranexamic acid is not eclipsed by drug-error mortality.

P-758 Evaluating mismatch categories and true errors using an electronic witnessing system

Abstract Study question What are the types and frequency of errors occurring in the laboratory identified by an electronic witnessing system (EWS)? Summary answer Several types of mismatch categories were identified, and the rate of a potentially catastrophic true mismatch error was < 1%. What is known already Mix-ups in the IVF laboratory have been recently highlighted in the media. These errors can have devastating long-term consequences for the fertility clinics and families involved. Prevention of these errors should be paramount in the laboratory. Study design, size, duration A retrospective analysis was conducted using 15 months of electronic witnessing data from two IVF laboratories in the United States. A total of 11,357 witnessed procedures were evaluated to determine the type and frequency of mismatches that occurred. Participants/materials, setting, methods All procedure match and mismatch data was recorded by an EWS (Matcher, IMT International). The mismatch data from two laboratories was evaluated to determine the category and occurrence of mismatches taking place in the assisted reproductive technology (ART) laboratory. Main results and the role of chance The overall mismatch rate was 0.78% (89/11,357). The types of mismatches were identified as: 1) Program: duplicate barcodes scanned, barcode misread by program, non-Matcher barcode picked up during scan, connectivity issues; 2) Wrong patient selected; 3) Transcription error; 4) Cycle set up: treatment cycle not set up correctly, donor not linked to treatment cycle; 5) True error: dishes and/or tubes from two different patients were in the same workstation at the same time. Program error happened most frequently at 0.30% (34/11,357). The wrong patient selected and cycle set up errors occurred 0.18% (20/11,357), followed by transcription error at 0.11% (12/11,357). A true error occurred 0.03% (3/11,357) and was rectified in < 10 seconds meaning there was no time for actual mixing of gametes to occur. These findings agree with previously published reports worldwide where the occurrence of a true mismatch is < 1%. Limitations, reasons for caution The present study retrospectively analyzed mismatch data gathered over a 15-month period after implementation of EWS. Further investigation is warranted to determine if mismatches occur more or less frequently after long term use of an EWS. Wider implications of the findings Failure to identify a true mismatch error may lead to a catastrophic error. Continued evaluation of EWS may provide insight into how and why a true error occurs. This information can then be utilized to improve laboratory protocols and procedures for enhanced patient protection. Trial registration number Not applicable

Resolving catastrophic error bursts from cosmic rays in large arrays of superconducting qubits

Scalable quantum computing can become a reality with error correction, provided coherent qubits can be constructed in large arrays. The key premise is that physical errors can remain both small and sufficiently uncorrelated as devices scale, so that logical error rates can be exponentially suppressed. However, energetic impacts from cosmic rays and latent radioactivity violate both of these assumptions. An impinging particle ionizes the substrate, radiating high energy phonons that induce a burst of quasiparticles, destroying qubit coherence throughout the device. High-energy radiation has been identified as a source of error in pilot superconducting quantum devices, but lacking a measurement technique able to resolve a single event in detail, the effect on large scale algorithms and error correction in particular remains an open question. Elucidating the physics involved requires operating large numbers of qubits at the same rapid timescales as in error correction, exposing the event's evolution in time and spread in space. Here, we directly observe high-energy rays impacting a large-scale quantum processor. We introduce a rapid space and time-multiplexed measurement method and identify large bursts of quasiparticles that simultaneously and severely limit the energy coherence of all qubits, causing chip-wide failure. We track the events from their initial localised impact to high error rates across the chip. Our results provide direct insights into the scale and dynamics of these damaging error bursts in large-scale devices, and highlight the necessity of mitigation to enable quantum computing to scale.

Reducing maritime accidents in ships by tackling human error: a bibliometric review and research agenda

Over the past decade the number of maritime transportation accidents has fallen. However, as shipping vessels continue to increase in size, one single incident, such as the oil spills from ‘super’ tankers, can have catastrophic and long-term consequences for marine ecosystems, the environment and local economies. Maritime transport accidents are complex and caused by a combination of events or processes that might ultimately result in the loss of human and marine life, and irreversible ecological, environmental and economic damage. Many studies point to direct or indirect human error as a major cause of maritime accidents, which raises many unanswered questions about the best way to prevent catastrophic human error in maritime contexts. This paper takes a first step towards addressing some of these questions by improving our understanding of upstream maritime accidents from an organisation science perspective—an area of research that is currently underdeveloped. This will provide new and relevant insights by both clarifying how ships can be described in terms of organisations and by considering them in a whole ecosystem and industry. A bibliometric review of extant literature of the causes of maritime accidents related to human error was conducted, and the findings revealed three main root causes of human and organisational error, namely, human resources and management, socio-technical Information Systems and Information Technologies, and individual/cognition-related errors. As a result of the bibliometric review, this paper identifies the gaps and limitations in the literature and proposes a research agenda to enhance our current understanding of the role of human error in maritime accidents. This research agenda proposes new organisational theory perspectives—including considering ships as organisations; types of organisations (highly reliable organisations or self-organised); complex systems and socio-technical systems theories for digitalised ships; the role of power; and developing dynamic safety capabilities for learning ships. By adopting different theoretical perspectives and adapting research methods from social and human sciences, scholars can advance human error in maritime transportation, which can ultimately contribute to addressing human errors and improving maritime transport safety for the wider benefit of the environment and societies ecologies and economies.

Human Factors Considerations in Satellite Operations Human-Computer Interaction Technologies: A Review of Current Applications and Theory

Satellite operations are a subset of remote operations that draw similarities with remotely piloted aircraft (RPA) and uncrewed aerial vehicle (UAV) operations. Increased research into boredom, complacency, habituation, and vigilance as they relate to satellite operations is required due to a lack of prevalence in the literature. Circadian rhythms, crew resource management, and shift work dynamics may exacerbate complacency-driven automation bias and social loafing errors in satellite operations. This overview of theory and applications aims to specifically focus on satellite operations literature within human factors research to identify areas requiring an expansion of knowledge. The human-in-the-loop commonality enables human factors lessons to be passed to satellite operations from unrelated sectors to mitigate catastrophic human error potentially. As such, this literature review details the need for increased research in satellite operations human factors.

Adaptive density-based clustering algorithm with shared KNN conflict game

Recently, density-based clustering algorithms have been garnering considerable attention in the unsupervised learning field as they can identify arbitrary cluster shapes. However, classical density-based algorithms are non-backtracking such as density-based spatial clustering of applications with noise (DBSCAN) and its improved variants. Therefore, the allocation of samples cannot be optimised during the clustering process. An incorrect division can cause subsequent errors. Furthermore, when the density is unevenly distributed, the globally uniform parameters will inevitably lead to catastrophic error consequences. To address these limitations, this study proposes an adaptive density-based clustering algorithm using the shared k-nearest neighbours (SKNN) conflict game (DC-SKCG). A local density-based adaptive cut-off distance-setting method is designed for the DC-SKCG, and a conflict game method based on SKNN is proposed to optimise the clustering process. Moreover, an automatic fusion mechanism for redundant high-density core regions is presented to (1) reduce the parameter sensitivity of the algorithm and (2) improve the parameter tolerance capacity. A series of experiments are conducted using various datasets demonstrate that DC-SKCG offers higher accuracy and robustness in most cases than state-of-the-art methods.

Identifying and Repairing Catastrophic Errors in Galaxy Properties Using Dimensionality Reduction

Abstract Our understanding of galaxy evolution is derived from large surveys designed to maximize efficiency by only observing the minimum amount needed to infer properties for a typical galaxy. However, for a few percent of galaxies in every survey, these observations are insufficient and derived properties can be catastrophically wrong. Further, it is currently difficult or impossible to determine which objects have failed, so that these contaminate every study of galaxy properties. We develop a novel method to identify these objects by combining the astronomical codes that infer galaxy properties with the dimensionality reduction algorithm t-SNE, which groups similar objects to determine which inferred properties are out of place. This method provides an improvement for the COSMOS catalog, which already uses existing techniques for catastrophic error removal, and therefore should improve the quality of large catalogs and any studies that are sensitive to large redshift errors.

Catastrophic Human Error in Assisted Reproductive Technologies: A Systematic Review.

Assisted reproductive technologies (ARTs) are complex processes with multiple and diverse opportunities for human error. Errors in ART are thought to be rare, but can have devastating consequences for patients and their offspring. The objectives of this article are to review known cases of human error in the ART laboratory and suggest preventative strategies. We performed a systematic review of the literature in accordance with Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines using PubMed and Google Scholar databases. Studies were eligible for inclusion if they involved known cases of unintentional human error in the ART laboratory. Only full-text articles in English were included. References of the resulted studies were considered for inclusion. A total of 420 articles were screened and 37 articles were selected for inclusion. These largely included case reports and reviews in the medical and legal literature. Twenty-two adverse events due to human error in the ART laboratory were identified. Eight of these adverse events were the result of the insemination with the wrong sperm, 6 errors lead to the transfer of the wrong embryo, 3 lead to an error in preimplantation genetic testing, and 5 adverse events lead to the failure of gamete and embryo cryostorage. Since the advent of ART, there have been reports of catastrophic events occurring secondary to human error in the laboratory to include incidents of unintended parentage, and have resulted in the loss of embryos and gametes through cryostorage failure. Proposed solutions include the stringent implementation and adherence to safety protocols, adequate laboratory staffing and training, and novel methods for specimen labeling and tracking. Of utmost importance is having knowledge of these errors and the ability to determine cause so that future events can be prevented.

OGLE-2017-BLG-0406: Spitzer Microlens Parallax Reveals Saturn-mass Planet Orbiting M-dwarf Host in the Inner Galactic Disk

Abstract We report the discovery and analysis of the planetary microlensing event OGLE-2017-BLG-0406, which was observed both from the ground and by the Spitzer satellite in a solar orbit. At high magnification, the anomaly in the light curve was densely observed by ground-based-survey and follow-up groups, and it was found to be explained by a planetary lens with a planet/host mass ratio of from the light-curve modeling. The ground-only and Spitzer-“only” data each provide very strong one-dimensional (1D) constraints on the 2D microlens parallax vector . When combined, these yield a precise measurement of and of the masses of the host and planet M planet = 0.41 ± 0.05 M Jup. The system lies at a distance D L = 5.2 ± 0.5 kpc from the Sun toward the Galactic bulge, and the host is more likely to be a disk population star according to the kinematics of the lens. The projected separation of the planet from the host is (i.e., just over twice the snow line). The Galactic-disk kinematics are established in part from a precise measurement of the source proper motion based on OGLE-IV data. By contrast, the Gaia proper-motion measurement of the source suffers from a catastrophic 10σ error.

Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling

Unsupervised domain adaptation aims to address the problem of classifying unlabeled samples from the target domain whilst labeled samples are only available from the source domain and the data distributions are different in these two domains. As a result, classifiers trained from labeled samples in the source domain suffer from significant performance drop when directly applied to the samples from the target domain. To address this issue, different approaches have been proposed to learn domain-invariant features or domain-specific classifiers. In either case, the lack of labeled samples in the target domain can be an issue which is usually overcome by pseudo-labeling. Inaccurate pseudo-labeling, however, could result in catastrophic error accumulation during learning. In this paper, we propose a novel selective pseudo-labeling strategy based on structured prediction. The idea of structured prediction is inspired by the fact that samples in the target domain are well clustered within the deep feature space so that unsupervised clustering analysis can be used to facilitate accurate pseudo-labeling. Experimental results on four datasets (i.e. Office-Caltech, Office31, ImageCLEF-DA and Office-Home) validate our approach outperforms contemporary state-of-the-art methods.

Semi-Supervised Learning under Class Distribution Mismatch

Semi-supervised learning (SSL) aims to avoid the need for collecting prohibitively expensive labelled training data. Whilst demonstrating impressive performance boost, existing SSL methods artificially assume that small labelled data and large unlabelled data are drawn from the same class distribution. In a more realistic scenario with class distribution mismatch between the two sets, they often suffer severe performance degradation due to error propagation introduced by irrelevant unlabelled samples. Our work addresses this under-studied and realistic SSL problem by a novel algorithm named Uncertainty-Aware Self-Distillation (UASD). Specifically, UASD produces soft targets that avoid catastrophic error propagation, and empower learning effectively from unconstrained unlabelled data with out-of-distribution (OOD) samples. This is based on joint Self-Distillation and OOD filtering in a unified formulation. Without bells and whistles, UASD significantly outperforms six state-of-the-art methods in more realistic SSL under class distribution mismatch on three popular image classification datasets: CIFAR10, CIFAR100, and TinyImageNet.

A Hybrid Downlink NOMA With OFDM and OFDM-IM for Beyond 5G Wireless Networks

In this paper, a hybrid power domain non-orthogonal multiple accessing (NOMA) scheme by the superposition of orthogonal frequency division multiple accessing (OFDM) and index modulated OFDM (OFDM-IM) technologies is presented and named IM-NOMA. It is shown via both computer-based simulations and mathematical analysis that IM-NOMA outperforms the classical OFDM-NOMA in terms of bit error rate (BER) under a total power constraint and achievable sum rate. The system performance of IM-NOMA not only depends on the power difference between the overlapping users but also on features of the OFDM-IM signal. Hence, this scheme is robust against possible catastrophic error performance in case similar power is assigned to the users.

Offline: Who should lead UNAIDS?

Who is best qualified to lead an organisation—UNAIDS— that has not only suffered severe reputational loss, but also faces threats to its continuing existence? UNAIDS is a jointly sponsored UN programme that has, in its own words, “led and inspired global, regional, national, and local leadership, innovation, and partnership to ultimately consign HIV to history”. But some observers believe this glorious history is just that—history. Rob Yates was recently appointed head of Chatham House's Centre on Global Health Security. He wrote on Twitter last week that a new Executive Director of UNAIDS should have the “courage and ability to wind up the organisation and integrate it into @WHO”. Kul Gautam, a former Deputy Executive Director of UNICEF, argued that “now it's time to question [UNAIDS] continuation”. Anthony Costello, most recently a Director at WHO, commented, “No one questions the need for a strong and distinct body for the HIV response. It's whether UNAIDS would function better under the democratic accountability of the World Health Assembly which might have prevented its shameful recent history”. Laurie Garrett, a Pulitzer-Prize winning writer on global health, noted that those selecting the next Executive Director “MUST define clearly why the world needs UNAIDS & how it should fit in the global health landscape.” Is it time to choose a leader who will close down UNAIDS? Maybe one day. But not now. Predictions about the end of AIDS have been badly misjudged. According to the Global Burden of Disease Study, there were almost 1 million deaths from AIDS in 2017. Those deaths occur throughout the lifecourse, but the toll is especially severe among 15–49-year-olds (676 100 deaths). There are almost 37 million people worldwide living with HIV. And the incidence remains shockingly high—1·9 million people newly infected every year. Although the number of AIDS-related deaths is projected to fall, even by 2040 those deaths will still be unacceptably high (742 million, with a worst-case scenario of 2·3 million deaths). The AIDS epidemic is at a critical moment. Decelerating the political response by extinguishing UNAIDS now would be a catastrophic error. There are five candidates: Salim Abdool Karim (an infectious diseases epidemiologist and Director of the Centre for the AIDS Programme of Research in South Africa); Sani Aliyu (physician, infectious diseases expert, and Director-General of Nigeria's National Agency for the Control of AIDS); Chris Beyrer (physician, HIV specialist, former President of the International AIDS Society, and Professor of Public Health and Human Rights at Johns Hopkins Bloomberg School of Public Health); Winnie Byanyima (engineer, politician, diplomat, and now Executive Director of Oxfam International); and Bernard Haufiku (physician and Namibia's former Minister of Health and Social Services). Each candidate has strengths. Aliyu spearheaded Nigeria's AIDS response under difficult political circumstances. Haufiku has ministerial experience. Byanyima knows how to run a complex global organisation. Karim is a highly respected HIV scientist whose work has transformed clinical practice. And Beyrer, whose partner died of AIDS in 1991, successfully uses human-rights approaches to protect and advance the health of marginalised communities in Asia, Africa, Latin America, Russia, and the US. There are disappointments. Only one woman? No forum for public debate and scrutiny? Appointment not election? The next Executive Director of UNAIDS must fulfil five criteria. First, s/he must have the personal integrity to restore trust and credibility to a damaged organisation—and to give governments confidence to invest in the AIDS response. Second, s/he must have proven scientific understanding of the AIDS epidemic in order to be able to use evidence as a platform for political advocacy. Third, s/he must have demonstrable ability to represent and engage with civil society. Fourth, s/he must be able to point to their commitment to key vulnerable populations. And finally, s/he must be able to show transformational leadership of a large organisation. The Programme Coordinating Board of UNAIDS met in Geneva last week and “commended the strong competencies of all short-listed candidates”. After interviews, a Committee of Cosponsoring Organisations will deliver no more than three names to the UN Secretary-General, António Guterres. It is no exaggeration to say that his choice may determine the future fate of the AIDS epidemic.

Reduced Rank Least Squares for Real-Time Short Term Estimation of Mean Arterial Blood Pressure in Septic Patients Receiving Norepinephrine.

Norepinephrine (NE), an endogenous catecholamine, is a mainstay treatment for septic shock, which is a life-threatening manifestation of severe infection. NE counteracts the loss in blood pressure associated with septic shock. However, an NE infusion that is too low fails to counteract the blood pressure drop, and an NE infusion that is too high can cause a hypertensive crisis and heart attack. Ideally, the NE infusion rate should maintain a patient’s mean arterial blood pressure (MAP) above 65 mmHg. There are a few data-driven, quantitative models to predict the MAP, and incorporate NE effects. This paper presents a model, driven by intensive care unit (ICU) measurable data and known NE inputs, to predict the future MAP of an ICU patient. We derive a least square estimation model for MAP based on available ICU data, including heart period, NE infusion rate, and respiration wave. We learn the parameters of our model from initial patient data and then use this information to predict future MAP data. We assess our model with data from 12 septic patients. Our model successfully predicts and tracks MAP when the NE infusion rate changes. Specifically, we predict MAP 3 to 20 min in the future with the mean error of less than 4 to 7 mmHg over 12 patients. Conclusion: this new approach creates the potential to advance methods for predicting NE infusion rate in septic patients. Significance: successfully predicted patients’ MAP could reduce catastrophic human error and lessen clinicians’ workload.

There Was No IS-LM Enigma: Both Keynes’s IS-LM(LP) and D-Z Models of Chapters 20 and 21 Together Make Up Keynes’s General Theory

All of J .M .Keynes’s earlier 1933-1935 versions of his IS-LM(LP) model contained a serious inconsistency. These earlier models all incorporated both actual and expected outcomes in the same model. The units did not match up. Keynes solved this problem by himself by splitting off the D-Z model from the IS-LM(LP) model. The D-Z model incorporated an analysis of expected results, expectations, uncertainty, and confidence.The major result that Keynes made use of in his analysis of the D-Z model was the Aggregate Supply Curve, which is a locus of all possible, expected D=Z outcomes. Only one of these expected outcomes could actually occur. The one outcome that actually occurred was called Y. Keynes then combined the actual Aggregate Income or Demand, Y, with r, the nominal long run rate of interest, to form the IS-LM(LP) model. The misbelief that IS-LM(LP) had to incorporate expectations in order to actually represent what Keynes meant was a catastrophic error made by the Pseudo Keynesians-Joan Robinson, Austin Robinson, Richard Kahn, and Roy Harrod, as well as by the economics profession at large. Unfortunately, no other economist, except Hugh Townshend, had grasped the necessary connections that had to exist between the two models.