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Fakes and counterfeits have existed since ancient times; and while the methods of forgery have surely advanced, so has the science necessary to identify them. Currency, art, and historical artifacts are only a few of the objects commonly forged; and scientists in forensic laboratories throughout the world work alongside artists, museums, linguists, and historians to authenticate these items. How to Identify a Forgery investigates how modern computers, printers, and scanners have presented new challenges for scientists and how objects suspected of being faked, forged, or fraudulent are examined forensically. How to Identify a Forgery contains information on: Counterfeiting currency Electronic and digital signatures Dating ink Dyes and pigments Forging art Handwriting analysis Scientific methodology Visual examination and microscopy How to Identify a Forgery contains illustrations, a glossary, and a detailed list of print and web resources. Sidebars on notable cases and pressing forensics issues throughout reinforce the text. Essential for students, teachers, collectors, and investigators who require information on proper forensic science practices, Dr. Bell's book is as fascinating as it is useful.

Intro -- Table of Contents -- Foreword -- Preface -- Acknowledgments -- Introduction -- A -- B -- C -- D -- E -- F -- G -- H -- I -- J -- K -- L -- M -- N -- O -- P -- Q -- R -- S -- T -- U -- V -- W -- X-Z -- Appendix I -- Appendix II -- Appendix III -- Index.

Intro -- Contents -- Preface -- Acknowledgments -- Introduction -- 1: History and Pioneers -- 2: The Scientific Approach -- 3: Dyes and Pigments -- Inks and Paints -- 4: Detecting Document Forgery -- 5: Counterfeiting Currency -- 6: Forging Art, History and Science -- 7: Conclusion: The Future of Fakes, Forgeries, and Counterfeits -- Glossary -- Further Reading -- Index.

Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- List of Figures -- List of Tables -- Preface -- Author -- 1 Forensic Measurements, Metrology, and Uncertainty -- 1.1 Consequence -- 1.2 The Best Way -- 1.3 Measurement Science and Traceability -- 1.4 Accuracy and Variability -- 1.5 Foundational Skills and Materials -- 1.6 Summary and Preview -- References -- 2 Sources of Uncertainty -- 2.1 Where Does Uncertainty Come From? -- 2.2 Diameter of a Penny -- 2.3 Weighing Pennies -- 2.4 The Need to Know -- 2.5 A Flowchart -- 2.6 The Elephant in the Room -- 2.7 Summary -- Further Reading -- 3 Foundational Concepts -- 3.1 Closeness to the True Value -- 3.2 Replicate Measurements and Spread -- 3.3 The Normal Distribution (and Others) -- 3.4 Figures of Merit -- 3.5 Summary and Preview -- References -- 4 Process and Procedures -- 4.1 Uncertainty Defined -- 4.2 Process of Uncertainty Estimation -- 4.3 Tools for Identifying Contributors: Measurement of�Density -- 4.4 Summary and Preview -- References -- 5 Measurement Assurance: Distances, Crime Scenes, and Firearms -- 5.1 Distance Measurement -- 5.2 Capturing Uncertainty -- 5.3 Firearms Measurements -- 5.4 Summary and Preview -- References -- 6 Uncertainty and�Weighing -- 6.1 How Balances Work -- 6.2 Buoyancy -- 6.3 Uncertainty Associated with the Balance -- 6.4 Balance Calibration -- 6.5 Uncertainty Budget with Balance Parameters -- 6.6 Uncertainty Budget with Parameters from a Calibration Certicfiate -- 6.7 Measurement Assurance and Control Chart Approach -- 6.8 Control Charts -- 6.9 Correlation of Events -- 6.10 Correlation and Weighing -- 6.11 Combined Example -- 6.12 Summary and Preview -- References -- 7 Breath Alcohol -- 7.1 Measuring Breath Alcohol -- 7.2 Dry Gas Calibration -- 7.3 Eeffctive Degrees of Freedom -- 7.4 Wet Gas Calibration -- 7.5 Uncertainty and Simulators -- 7.6 Field Use and Uncertainty -- 7.7 Summary and Preview -- References -- 8 Miscellaneous Topics -- 8.1 Quantitative Analysis -- 8.2 Sampling -- 8.3 Sensitivity Coefficients -- 8.4 Uncertainty and Equations -- 8.5 Accuracy and Uncertainty -- 8.6 Summary -- References -- Index -- A -- B -- C -- D -- E -- F -- G -- H -- I -- K -- L -- M -- N -- O -- P -- Q -- R -- S -- T -- U -- V -- W.

Intro -- Contents -- Acknowledgments -- Introduction -- 1: History and Guiding Principles of Forensic Engineering Science -- 2: Accident Reconstruction: Getting Started -- 3: Accident Reconstruction: Moving into High Gear -- 4: Speed from Critical-Speed Scuffs -- 5: Murder Poorly Disguised as an Accident -- 6: Subway Stop -- 7: The Grounding of the Merchant Vessel Tamano -- 8: Crane Collapse -- 9: Scaffolding Collapse -- 10: Bringing It All Together -- Conclusion -- Glossary -- Further Reading -- Index.

Intro -- Contents -- Preface -- Acknowledgments -- Introduction -- 1: Forensic Science: In and Out of the Laboratory -- 2: History and Pioneers -- 3: What Is Evidence? -- 4: Microscopy -- 5: Spectroscopy -- 6: Chromatography -- 7: Forensic DNA -- 8: Fingerprints -- 9: Firearms Examination -- 10: Testimony and Report Writing -- Conclusion -- Chronology -- Glossary -- Further Reading -- Index.

AbstractAlthough induced abortion is common, measurement issues have long made this area of research challenging. The current analysis applies an indirect method known as the list experiment to try to improve survey‐based measurement of induced abortion. We added a double list experiment to a population‐based survey of reproductive age women in Rajasthan, India and compared resulting abortion estimates to those we obtained via direct questioning in the same sample. We then evaluated list experiment assumptions. The final sample completing the survey consisted of 6,035 women. Overall, 1.8 percent of the women reported a past abortion via the list experiment questions, whereas 3.5 percent reported an abortion via the direct questions, and this difference was statistically significant. As such, the list experiment failed to produce more valid estimates of this sensitive behavior on a population‐based survey of reproductive age women in Rajasthan, India. One explanation for the poor list experiment performance is our finding that key assumptions of the methodology were violated. Women may have mentally enumerated the treatment list items differently from the way they enumerated control list items. Further research is required to determine whether researchers can learn enough about how the list experiment performs in different contexts to effectively and consistently leverage its potential benefits to improve measurement of induced abortion.

We estimate the relationship between unmet need for contraception and coital frequency using data from the most recent Standard Demographic and Health Surveys conducted from 2005 to 2015. Individual‐level analyses include 55 countries (n=245,732 women). The dependent variable is women's report of any sex in the last four weeks; the independent variable is current unmet need. Bivariate ecological results using country averages indicate that prevalence of unmet need is significantly negatively correlated with the proportion reporting recent sexual activity. Multivariate regression of individual‐level data show that the overall odds ratio of having had sex in the last four weeks is 3.23 and 2.97 for women with met contraceptive need for spacing and limiting fertility, respectively, compared with women with unmet contraceptive need. These results suggest that current estimates of unmet need exaggerate the risk of unintended pregnancy because coital frequency is not uniform with respect to unmet need. Findings also suggest that, despite being categorized as having unmet need, many women may still be taking measures to control their fertility through regulating the tempo of marital coitus, thus reducing their risk of unintended pregnancy.

AbstractFertility researchers rely upon a simple binary: pregnant versus not pregnant. However, this conceptualization does not capture many women's experiences, both historically and in numerous settings today. We suggest that pregnancy status may be a much more ambiguous state, and that such ambiguity is often productive for women. Building a culturally sensitive understanding of what we are calling "productive ambiguity" can foster more rigorous studies of fertility that better capture potential pregnancy and the range of post‐coital fertility‐inhibiting actions women take, both intentionally and not. In this paper, we aim to: 1) describe the ambiguity that exists around pregnancy; 2) explain the ways in which this ambiguity is productive for women; 3) analyze two concrete examples of such ambiguity in practice: the case of menstrual regulation and the unexpected conceptual overlaps between contraception and early abortion in a variety of settings, and finally; 4) suggest ways that this more nuanced understanding might inform fertility research, including abortion measurement research. We combine recent qualitative and quantitative data with historical sources to analyze the cultural logics and power dynamics of this ambiguity.

Using a longitudinal design, the authors examined the criterion-related validity of two operationalizations of task-specific team efficacy that differed in their approximation to the level of analysis of the criterion, team performance. Data were obtained from 85 highly interdependent dyadic teams trained over a 2-week period to perform a complex perceptual-motor skill task. Results indicated that, as expected, the operationalization with a team-level referent (referent-shift consensus) was superior to the operationalization with an individual-level referent (additive) across all three data collection periods. For the referent-shift consensus operationalization, within-team agreement and the criterion-related validity improved between the first and second data collection periods but not between the second and third. However, for both operationalizations, despite the increased strength of the team efficacy and team performance relationships, efficacy ratings collected later in the study protocol did not explain unique variance in subsequent team performance once the effect of previous performance was statistically controlled.

AbstractDespite induced abortion being broadly legal in India, up‐to‐date information on its frequency and safety is not readily available. Using direct and indirect methodological approaches, this study measures the one‐year incidence and safety of induced abortions among women in the state of Rajasthan. The analysis utilizes data from a population‐based survey of 5,832 reproductive aged women who reported on the abortion experiences of their closest female confidante in addition to themselves. We separately assess correlates of having a recent and most unsafe abortion using multivariable regression models. The confidante approach produced a one‐year abortion incidence estimate of 23 per 1,000 women, whereas the respondent estimate is 9.5 per 1,000 women. Based on the confidante estimate, approximately 441,000 abortions occurred in Rajasthan over a year. Overall, 25 and 29 percent of respondent and confidante reported abortions were classified as most unsafe. Results suggest that abortion remains an integral component of women's fertility regulation, and that a liberal law alone is insufficient to guarantee access to safe abortion services. Existing policies on abortion in India need updating to permit task sharing in line with current recommendations to expand service delivery so that demand is met through provision of safe and accessible services.