Infinity and the Brain proposes a logical and scientific way to resolve the paradox of mind and matter -- by explaining how the perception of a finite image is dependent upon the contrasting infinitude of God. The theory holds that awareness is equal to a tension between existence and nonexistence, such that the self is illuminated to itself (becomes conscious) to the exact measure that it anticipates the infinitude of its own nonexistence. This "anticipation" is actually a "tendency toward" a (...) loss of structure in accordance with the second law of thermodynamics, a process that is restrained by effort and the consequent wholesness of an image. An understanding of how effort is linked to an image and how both are dependent upon neural systems inseparable from "infinity anticipation" sets the stage for a new worldview -- in which mind is seen as dependent upon the immanence of an infinite God. And because "mind" can be defined by the presence of an image which intrinsically restrains disorder, we see by extrapolation that the entire universe must be fundamentally personal, not objective as currently viewed by modern science. Book jacket. (shrink)

Contemporary analytic philosophy recognizes few principled constraints on its subject matter. When other disciplines also lay claim to a particular topic, however, important questions arise concerning the relation between these other disciplines and philosophy. A case in point is mathematics: traditional philosophy of mathematics defines a set of problems and certain general answers to those problems. However, mathematics is a subject matter that can be studied in many other ways: historically, sociologically, or even aesthetically, for example. Given this, we may (...) ask what implications discoveries in these disciplines have for the philosophy of mathematics. (shrink)

The debate over futility is driven, in part, by physicians' desire to recover some measure of decision-making authority from their patients. The standard approach begins by noting that certain interventions are futile for certain patients and then asserts that doctors have no obligation to provide futile treatment. The concept of futility is a complex one, and many commentators find it useful to distinguish ‘physiological futility’ from ‘qualitative futility’. The assertion that physicians can decide to withhold physiologically futile treatment generates little (...) controversy. The claim that they can withhold qualitatively futile treatment runs afoul of standard objections to medical paternalism. There is reason to believe that the conceptual distinction will not be maintained in clinical practice. This paper contends that the scientific data which would support a physician's unilateral decision to withhold physiologically futile treatment also provide support for an institutional policy restricting access to the treatment. The data the doctor uses to take decision-making power out of the hands of the patient can be used by the administrator to take power out of the hands of the doctor. While this loss of power is unproblematic, there is reason to believe that the ambiguity in the term ‘futility’ will allow a much greater loss of physicians' power. Keywords: futility, physician authority CiteULike Connotea Del.icio.us What's this? (shrink)

Aristotelian ethics is widely accepted by many scholars as a practical science. However, this study showed that it is not after all a practical science but a speculative or theoretical science. Having employed textual analysis on Aristotle’s Nicomachean Ethics, it was found out that eudaimonia the Highest Good/Chief Good which is the ultimate goal of Ethics is achieved not through action but through contemplation. Contemplation is the act not of the will but of intellect. Hence, the highest virtue or excellence (...) of man is the fulfilment of highest faculty which is reason in contemplation of the Chief Good. The Chief Good, which is characterized by Aristotle as final, complete, and Self-Sufficient End is not physical and concrete but rather incorporeal and abstract because such qualities cannot be found among corporeal entities. Thus, Aristotelian ethics is metaphysics; it is neither concrete nor practical. Moreover, happiness cannot be the Chief Good because happiness is merely an activity, a quality, and a disposition and an activity cannot be identified as end which is desired for its own sake. Therefore, the Chief Good must be a substance and this substance is the Final Cause/the Necessary Being which is the End of all ends and the Good of all goods. KEYWORDS: Philosophy, Aristotle, Ethics, Nicomachean Ethics, Moral Philosophy, Metaphysics,Theoretical Science, Speculative Science, Descriptive Textual Analysis, Philippines. (shrink)

The orthodox way of Mass Communication and Journalism education is to letstudents undergo three years of lecture and have their internship on the fourth orlast year of their college life. The process is effective, but there is a faster and a moreeffective way to learn news writing. The phenomenological Approach to writing newswould allow students to learn the rudiments of writing news article through thereverse process of immersion to the field and later expound the phenomena thatthey went through during their (...) exposure in the context of journalistic discipline. The Phenomenological Approach to writing news article is the fastest and mosteffective way to teach students write news article because they would be exposedto the phenomena of identifying the topic to write about, interviewing of sources,weeding out of non-essential details and putting together the information into onecoherent article. Expounding the phenomena that the students went through allowsthe students to absorb journalistic values easily by relating their experience to thetheories of good journalism during the workshop. Keywords: Mass Communication, newswriting, phenomenological approach, journalism,news-writing workshop, news writing internship, descriptive-qualitative design,Philippines. (shrink)

RésuméDans leur livre récent, George Lakoff et Rafael Núñez se livrent à une critique naturaliste soutenue du platonisme traditionnel concernant les entités mathématiques. Ils affirment que des résultats récents en sciences cognitives démontrent qu'il est faux. En particulier, ils estiment que la découverte que la cognition mathématique s'appuie pour une large part sur les métaphores conceptuelles est incompatible avec le platonisme. Nous montrons ici que tel n'est pas le cas. Nous examinons et rejetons également quelques arguments philosophiques que formulent Lakoff (...) et Núñez contre le platonisme. Enfin, nous lions leur hostilité au platonisme à certaines opinions sur les ramifications politiques de celui-ci. Pour conclure, nous faisons valoir que ces opinions sont sans fondements et présentent une image distordue des dimensions politiques du platonisme. (shrink)

Hospital ethics committees must be knowledgeable if they are to perform consultations, advise administrators on policy, or offer educational programs. Because the membership of the committee is interdisciplinary, with most drawn from the healthcare professions, the individuals who join cannot be expected to bring knowledge of bioethies with them. Therefore, a new committee must spend time developing expertise before it can appropriately serve the hospital community. Although the need for committee self-education is generally recognized, it is seldom discussed in any (...) detail. When discussed at all, expertise in bioethies is usually described as composed of a familiarity with an identifiable body of knowledge and mastery over techniques of moral reasoning. It is assumed that a committee can develop this expertise early in its life through a short course of study. (shrink)

Professions have traditionally treated advocacy as a collective duty, best assigned to professional associations to perform. In North American nursing, advocacy for issues affecting identifiable patients is assigned instead to their nurses. We argue that nursing associations’ withdrawal from advocacy for patient care issues is detrimental to nurses and patients alike. Most nurses work in large institutions whose internal policies they cannot influence. When these create obstacles to good care, the inability of nurses to affect change can result in avoidable (...) distress for them and for their patients. We illustrate this point with a case study: the circumstances of the death of Michael Joseph LeBlanc, an inmate at Kingston Penitentiary Regional Hospital (Ontario). We conclude that patients and their nurses will suffer unnecessarily unless or until nursing associations cease to burden individual nurses with the responsibility for patient advocacy. (shrink)

Numerous searches have failed to identify a single co-occurrence of total blindness and schizophrenia. Evidence that blindness causes loss of certain NMDA-receptor functions is balanced by reports of compensatory gains. Connections between visual and anterior cingulate NMDA-receptor systems may help to explain how blindness could protect against schizophrenia.

ObjectiveTo compare techniques for computing clustering and switching scores in terms of agreement, correlation, and empirical value as predictors of incident cognitive impairment.MethodsWe transcribed animal and letter F fluency recordings on 640 cases of ICI and matched controls from a national epidemiological study, amending each transcription with word timings. We then calculated clustering and switching scores, as well as scores indexing speed of responses, using techniques described in the literature. We evaluated agreement among the techniques with Cohen’s κ and calculated (...) correlations among the scores. After fitting a base model with raw scores, repetitions, and intrusions, we fit a series of Bayesian logistic regression models adding either clustering and switching scores or speed scores, comparing the models in terms of several metrics. We partitioned the ICI cases into acute and progressive cases and repeated the regression analysis for each group.ResultsFor animal fluency, we found that models with speed scores derived using the slope difference algorithm achieved the best values of the Watanabe–Akaike Information Criterion, but with good net reclassification improvement only for the progressive group. For letter fluency, different models excelled for prediction of acute and progressive cases. For acute cases, NRI was best for speed scores derived from a network model, while for progressive cases, the best model used clustering and switching scores derived from the same network model. Combining variables from the best animal and letter F models led to marginal improvements in model fit and NRI only for the all-cases and acute-cases analyses.ConclusionSpeed scores improve a base model for predicting progressive cognitive impairment from animal fluency. Letter fluency scores may provide complementary information. (shrink)

This article traces the continuities in Pocock's work from his early exploration of the 'common law mind' to his recent work calling for a rethinking of English history and an appreciation of its British context. His work is understood here as the product of perspectives available to him as a New Zealander made aware by his own history of the central roles in all human history played by the movement of people across continents and (especially) across oceans, and by the (...) ways in which different cultures situate themselves in time. Pocock's exploration of the history of 'political thought' has, indeed, often been concerned most with that form of political thinking and identity formation that was rooted in a society's understanding of its own past. This is the key continuity explored in the article. (shrink)

THE ART OF CAUSAL CONJECTURE Glenn Shafer Table of Contents Chapter 1. Introduction........................................................................................ ...........1 1.1. Probability Trees..........................................................................................3 1.2. Many Observers, Many Stances, Many Natures..........................................8 1.3. Causal Relations as Relations in Nature’s Tree...........................................9 1.4. Evidence............................................................................................ ...........13 1.5. Measuring the Average Effect of a Cause....................................................17 1.6. Causal Diagrams..........................................................................................20 1.7. Humean Events............................................................................................23 1.8. Three Levels of Causal Language................................................................27 1.9. An Outline of the Book................................................................................27 Chapter 2. Event Trees............................................................................................... .....31 2.1. Situations and Events...................................................................................32 2.2. The Ordering of Situations and Moivrean Events.......................................35 2.3. Cuts................................................................................................ ..............39 2.4. Humean Events............................................................................................43 (...) 2.5. Moivrean Variables......................................................................................49 2.6. Humean Variables........................................................................................53 2.7. Event Trees for Stochastic Processes...........................................................54 2.8. Timing in Event Trees.................................................................................56 2.9. Intersecting Event Trees...............................................................................60 2.10. Notes on the Literature...............................................................................61 Chapter 3. Probability Trees...........................................................................................63 3.1. Some Types of Probability Trees.................................................................64 ii 3.2. Axioms for the Probabilities of Moivrean Events.......................................68 3.3. Zero Probabilities....................................................................................... ..70 3.4. A Sample-Space Analysis of the Event-Tree Axioms.................................72 3.5. Probabilities and Expected Values for Variables.........................................74 3.6. Martingales......................................................................................... .........79 3.7. The Expectation of a Variable in a Cut........................................................83 3.8. Conditional Expected Value and Conditional Expectation.........................87 Chapter 4. The Meaning of Probability...........................................................................91 4.1. The Interpretation of Expected Value..........................................................92 4.2. The Interpretation of Expectation................................................................95 4.3. The Long Run..............................................................................................98 4.4. Changes in Belief.........................................................................................101 4.5. The Empirical Validation of Probability......................................................106 4.6. The Diversity of Uses of Probability...........................................................108 4.7. Notes on the Literature.................................................................................110 Chapter 5. Independent Events.......................................................................................113 5.1. Independence........................................................................................ .......114 5.2. Weak Independence.....................................................................................118 5.3. The Principle of the Common Cause...........................................................121 5.4. Conditional Independence............................................................................128 5.5. Notes on the Literature.................................................................................133 Chapter 6. Events Tracking Events.................................................................................135 6.1. Tracking............................................................................................ ...........137 6.2. Tracking and Conditional Independence.....................................................142 6.3. Stochastic Subsequence...............................................................................143 6.4. Singular Diagrams for Stochastic Subsequence...........................................147 6.5. Conjunctive and Interactive Forks...............................................................149 Chapter 7. Events as Signs of Events..............................................................................153 iii 7.1. Sign................................................................................................ ..............154 7.2. Weak Sign................................................................................................ ....159 7.3. The Ethics of Causal Talk............................................................................160 7.4. Screening Off...............................................................................................16 2 Chapter 8. Independent Variables...................................................................................167 8.1. Unconditional Independence........................................................................170 8.2. Conditional Independence............................................................................175 8.3. Independence for Partitions.........................................................................177 8.4. Independence for Families of Variables......................................................182 8.5. Individual Properties of the Independence Relations...................................186 Chapter 9. Variables Tracking Variables........................................................................189 9.1. Tracking and Conditional Independence: A Summary...............................190 9.2. Strong Tracking............................................................................................ 192 9.3. Strong Tracking and Conditional Independence..........................................198 9.4. Stochastic Subsequence...............................................................................201 9.5. Functional Dependence................................................................................203 9.6. Tracking in Mean.........................................................................................204 9.7. Linear Tracking............................................................................................ 207 9.8. Tracking by Partitions..................................................................................210 9.9. Tracking by Families of Variables...............................................................212 Chapter 10. Variables as Signs of Variables...................................................................215 10.1. Sign................................................................................................ ............219 10.2. Linear Sign................................................................................................ .222 10.3. Scored Sign................................................................................................ 225 10.4. Families of Variables.................................................................................227 Chapter 11. AnTheory of Event Trees.............................................................229 11.1. Event Trees as Sets of Sets........................................................................230 11.2. Event Trees as Partially Ordered Sets........................................................232 iv 11.3. Regular Event Trees...................................................................................240 11.4. The Resolution of Moivrean Variables......................................................244 11.5. Humean Events and Variables...................................................................246 Chapter 12. Martingale Trees..........................................................................................247 12.1. Examples of Decision Trees......................................................................249 12.2. The Meaning of Probability in a Decision Tree.........................................253 12.3. Martingales......................................................................................... .......257 12.4. The Structure of Martingale Trees.............................................................261 12.5. Probability and Causality...........................................................................265 12.6. Lower and Upper Probability.....................................................................269 12.7. The Law of Large Numbers.......................................................................272 12.8. Notes on the Literature...............................................................................274 Chapter 13. Refining............................................................................................ ...........275 13.1. Examples of Refinement............................................................................277 13.2. A Constructive Definition of Finite Refinement.......................................281 13.3. Axioms for Refinement..............................................................................282 13.4. Lifting Moivrean Events and Variables.....................................................288 13.5. Refining Martingale Trees.........................................................................288 13.6. Grounding........................................................................................... .......294 Chapter 14. Principles of Causal Conjecture..................................................................299 14.1. The Diversity of Causal Explanation.........................................................302 14.2. The Mean Effect of the Happening of a Moivrean Event..........................305 14.3. The Effect of a Humean Variable..............................................................311 14.4. Attribution and Generality.........................................................................316 14.5. The Statistical Measurement of the Effect of a Cause...............................319 14.6. Measurement by Experiment.....................................................................320 14.7. Using Our Knowledge of How Things Work............................................322 v 14.8. Sampling Error...........................................................................................329 14.9. The Sampling Frame..................................................................................329 14.10. Notes on the Literature.............................................................................330 Chapter 15. Causal Models.............................................................................................3 31 15.1. The Causal Interpretation of Statistical Prediction....................................333 15.2. Generalizing to a Family of Exogenous Variables....................................337 15.3 Some Joint Causal Diagrams......................................................................339 15.4. Causal Path Diagrams................................................................................342 15.5. Causal Relevance Diagrams.......................................................................346 15.6. The Meaning of Latent Variables..............................................................352 15.7. Notes on the Literature...............................................................................357 Chapter 16. Representing Probability Trees...................................................................359 16.1. Three Graphical Representations...............................................................361 16.2. Skeletal Simplifications.............................................................................368 16.3. Martingale Trees in Type Theory...............................................................371 Appendix A. Huygens’s Probability Trees.....................................................................379 Huygens’s Manuscript in Translation..................................................................380 Appendix B. Some Elements of Graph Theory..............................................................385 B1. Undirected Graphs........................................................................................385 B2. Directed Graphs............................................................................................38 6 Appendix C. Some Elements of Order Theory...............................................................393 C1. Partial and Quasi Orderings.........................................................................393 C2. Singular and Joint Diagrams for Binary Relations.......................................394 C3. Lattices............................................................................................ .............395 C4. The Lattice of Partitions of a Set..................................................................396 Appendix D. The Sample-Space Framework for Probability.........................................399 D1. Probability Measures....................................................................................399 D2. Variables........................................................................................... ...........400 vi D3. Families of Variables...................................................................................401 D4. Expected Value............................................................................................402 D5. The Law of Large Numbers.........................................................................405 D6. Conditional Probability................................................................................406 D7. Conditional Expected Value........................................................................407 Appendix E. Prediction in Probability Spaces................................................................409 E1. Conditional Distribution...............................................................................411 E2. Regression on a Single Variable...................................................................412 E3. Regression on a Partition or a Family of Variables......................................415 E4. Linear Regression on a Single Variable.......................................................418 E5. Linear Regression on a Family of Variables................................................422 Appendix F. Sample-Space Concepts of Independence.................................................425 F1. Overview............................................................................................ ...........426 F2. Independence Proper.....................................................................................432 F3. Unpredictability in Mean..............................................................................434 F4. Simple Uncorrelatedness..............................................................................437 F5. Mixed Uncorrelatedness...............................................................................438 F6. Partial Uncorrelatedness...............................................................................440 F7. Independence for Partitions..........................................................................442 F8. Independence for Families of Variables.......................................................445 F9. The Basic Role of Uncorrelatedness.............................................................448 F10. Dawid’s Axioms.........................................................................................449 Appendix G. Prediction Diagrams..................................................................................453 G1. Path Diagrams............................................................................................ ..454 G2. Generalized Path Diagrams..........................................................................462 G3. Relevance Diagrams.....................................................................................466 G4. Bubbled Relevance Diagrams......................................................................475 Appendix H. Abstract Stochastic Processes...................................................................479 vii H1. Probability Conditionals and Probability Distributions...............................477 H2. Abstract Stochastic Processes......................................................................479 H3. Embedding Variables and Processes in a Sample Space.............................480 References.......................................................................................... ..............................491. (shrink)

Political obligation is concerned with the clash between the individual’s claim to self-governance and the right of the state to claim obedience. It is a central and ancient problem in political philosophy. In this authoritative introduction, Dudley Knowles frames the problem of obligation in terms of the duties citizens have to the state and each other. Drawing on a wide range of key works in political philosophy, from Thomas Hobbes, John Locke, David Hume and G. W. F. Hegel to (...) John Rawls, A. John Simmons, Joseph Raz and Ronald Dworkin, Political Obligation: A Critical Introduction is an ideal starting point for those coming to the topic for the first time, as well as being an original and distinctive contribution to the literature. Knowles distinguishes the philosophical problem of obligation - which types of argument may successfully ground the legitimacy of the state and the duties of citizens - from the political problem of obligation - whether successful arguments apply to the actual citizens of particular states. Against the anarchist and modern skeptics, Knowles claims that a plurality of arguments promise success when carefully formulated and defended, and discusses in turn ancient and modern theories of social contract and consent, fairness and gratitude, utilitarianism, justice and a Samaritan duty of care for others. Against modern communitarians, he defends a distinctive liberalism: ‘the state proposes, the citizen disposes’. (shrink)

Hegel is notable for his distinctive contribution to the perennial concerns of political philosophy. The essays in this volume bring together some of the finest interpreters of Hegel writing in English, explore his distinguished heritage and explain its contemporary relevance.

Synofzik, Vosgerau, and Newen (2008) offer a powerful explanation of the sense of agency. To argue for their model they attempt to show that one of the standard models (the comparator model) fails to explain the sense of agency and that their model offers a more general account than is aimed at by the standard model. Here I offer comment on both parts of this argument. I offer an alternative reading of some of the data they use to argue against (...) the comparator model. I argue that contrary to Synofzik, Vosgerau and Newen’s reading the case of G.L. supports rather than contradicts the comparator model. Next I suggest how the comparator model can differentiate failures of action attribution in patients suffering parietal lobe lesions and delusions of alien control. I also argue that the apparently unexpected phenomenon of ‘‘hyperassociation” is predicted by the comparator model. Finally I suggest that as it stands Synofzik, Vosgerau and Newen’s model is not well specified enough to explain deficits in the sense of agency associated with delusions of thought insertion. Thus they have not met their second argumentative burden of showing how their model is more general than the comparator model. (shrink)

In JAP 9 (1992) Gordon Graham argued that liberals cannot be counted on to support democratic institutions since there are no conceptual or strongly contingent links between democracy and liberal ideals. This paper responds to Graham's challenge by claiming that his model of liberal aristocracy is not liberal in several respects. In particular, the liberal should recognise a right to democratic participation which individuals may plausibly claim as an element in a respectable conception of how to live well. The right (...) to democratic participation is shown to stand alongside other important liberal ideals which may be justified in this fashion, e.g. freedom of religious worship and freedom of association. Furthermore, I argue against those who claim that political participation enacts delusory aspirations that the rights which are promoted and protected within a democratic constitution are necessary for both individual and collective autonomy — and so the liberal should defend them. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Kennedy Institute of Ethics Journal 10.1 (2000) 103-108 [Access article in PDF] Letters "Small Sacrifices" in Stem Cell Research Madam: I agree with Professors McGee and Caplan (in their article "The Ethics and Politics of Small Sacrifices in Stem Cell Research," KIEJ, June 1999) that the question of the nature and status of the source of stem cells must be addressed. However, in their eagerness to convince us of (...) the smallness of the sacrifices, I think the authors use some unfortunate rhetorical devices and move much too quickly over some necessary distinctions.The rhetorical display is unfortunate if the article is intended to be a fair and rational development of an argument--e.g., those who hold a position in opposition to the authors do not argue they "inveigh." The section on the political area of the controversy seems particularly dismissive of other's positions.However, I will focus on just two areas where I think a more nuanced consideration would make the question of the moral legitimacy of the "small sacrifices" of embryos less obvious than the authors' rhetoric would suggest.First, they claim that opponents of such research assume some sort of "super status" for an embryo. The rights generally conceded to born human beings may not be as "weak" as they characterize. But even considering only the "negative right against unwarranted violence," I think the authors misdescribe the situation. Contrary to their assertion, I do not know when "adults and even children are... forced to give life... in the defense or at least interest of the community's highest ideals and most pressing interests" (p. 153). Could they be speaking of capital punishment, justified in the name of protecting the community? But then why mention children?It is true that not everyone can be guaranteed every means to preserving and enhancing life. But this limitation on positive rights is not a "forced giving." Adults may be compelled to risk life--e.g. in a draft for the sake of a war. But, again, the more or less justifiable imposition of a risk is not the same as selecting out one particular individual or class to be directly killed. Neither adults nor born children are compelled to be killed for the sake of organ "donation," even if a greater number might be saved. If one grants equivalent status to the embryo (as the authors seem to do here for the sake of argument), opponents do not have to claim a "super status" for embryos, just the ordinary human right not to be killed even for "compassionate" motives.A second area where I think the authors move too quickly is in their impoverished definition of the essential humanity of the early embryo as exhaustively represented by the physical structure of its DNA. The authors seem to recognize [End Page 103] that, ordinarily, there is more to personhood than sheer physical structure. For example, they mention memories and habits (p. 154). They could also speak of relationships, attitudes, and the like. Since an early embryo has no such components of personality as we experience it, the authors hold that its identity could only be contained in its DNA. Since this DNA is preserved, even spread far and wide, by the use of stem cells, it almost seems as if we are doing the early embryo a favor by breaking it up.However, just because the embryo does not have any conscious memories or other attributes of character or personality, that does not mean its identity is constituted only by its physical structure described statically. The early embryo is not just a bundle of discrete structures, and its DNA is not just an inert lump made up of certain smaller lumps. Both the embryo and its DNA are active. Thus the identity of even an early embryo includes both its current processes and the innate potential for further activity and development. Although lacking a conscious will, the early embryo is already in a sense an agent, already doing things--growing, changing, and heading toward something that... (shrink)

In JAP 9 (1992) Gordon Graham argued that liberals cannot be counted on to support democratic institutions since there are no conceptual or strongly contingent links between democracy and liberal ideals. This paper responds to Graham's challenge by claiming that his model of liberal aristocracy is not liberal in several respects. In particular, the liberal should recognise a right to democratic participation which individuals may plausibly claim as an element in a respectable conception of how to live well. The right (...) to democratic participation is shown to stand alongside other important liberal ideals which may be justified in this fashion, e.g. freedom of religious worship and freedom of association. Furthermore, I argue against those who claim that political participation enacts delusory aspirations that the rights which are promoted and protected within a democratic constitution are necessary for both individual and collective autonomy — and so the liberal should defend them. (shrink)

The Sarbanes–Oxley (SOX) Act was passed in 2002 in response to various instances of corporate malfeasance. The Act, designed to protect investors, led to wide-ranging regulation over various actions of managers, auditors and investment analysts. Part of SOX, and the focus of this study, targeted the disclosure by firms of “pro forma” earnings, an alternate (from GAAP earnings), flexible and unaudited measure of firm performance. Specifically, SOX directed the Securities and Exchange Commission (SEC) to craft regulation which would reduce – (...) and preferably eliminate – any pro forma earnings disclosure which might be “misleading”. Examining earnings press releases over a 3-year period, this study addresses three questions. Were firms disclosing pro forma in a potentially misleading manner, what was the nature of this potentially misleading disclosure, and did SOX affect the disclosure practices? We find the following. In 2001 (prior to SOX), 53 firms – over 10% of all U.S. S&P 500 firms – were disclosing pro forma earnings in a potentially misleading manner. This was being done most commonly by using traditional GAAP terminology (e.g., “net income”) in the press release headline to describe what was later in the press release revealed to be a pro forma amount (i.e., “net income excluding special items”). By 2003 (subsequent to the SEC regulation), potentially misleading disclosure practices were seen in less than 1% of the earnings press releases of S&P 500 firms. This significant reduction suggests that managers, prior to the regulation, were either careless in their pro forma reporting practice, or were intentionally – and unethically – attempting to mislead investors. Either way, we conclude that the SEC regulation was both necessary and effective. (shrink)