Respect for others a key for Supreme Court nominee Sheilah Martin

first_imgOTTAWA – Being a good listener and ensuring people know that they’ve been heard are keys to earning public confidence as a judge, Supreme Court nominee Sheilah Martin said Tuesday during a question-and-answer session with parliamentarians.Martin, who was named last week as the Trudeau government’s latest high court appointee, stressed the importance of thoughtfully considering all sides as an independent arbiter.“I think judges need to show respect to get respect,” she said. “And it has been my personal goal to be respectful in court, and to listen patiently and to let things unfold.”Martin said she hopes her written judgments make it clear that a losing party’s arguments have been fully understood. “I want to write that way, so that somebody would say, ‘Oh, OK, I was in good hands.’”Tuesday’s session included members of the House of Commons justice committee and the Senate legal and constitutional affairs committee, as well as representatives of the Bloc Quebecois and the Green party.Martin was politely peppered with questions about the Charter of Rights and Freedoms, jurors, victims, the environment, terrorism and sexual assault. She carefully phrased her answers to avoid any appearance of bias.University of Ottawa law professor Francois Larocque, moderator of the session, warned at the outset that Martin could not comment on matters that might come before the Supreme Court, nor cases she has already presided over as a provincial and territorial judge.Larocque billed it as a chance to get to know Martin better rather than a cross-examination — an opportunity for MPs and senators to ensure Martin “has the proverbial right stuff” to sit on Canada’s highest court.Martin displayed her comfort in both of Canada’s official languages, revealed an abiding love of teaching and showed flashes of wit.Asked about the legacy she wanted to leave, Martin replied, “I would hope that people said that I listened carefully, and that I was a deep thinker and that I had really nice hair.”Martin grew up in Montreal was trained in both civil and common law before moving to Alberta to pursue her career as an educator, lawyer and judge.From 1991 to 1996 she was acting dean and then dean of the University of Calgary’s faculty of law. Martin went on to practise criminal and constitutional law, and became a judge in 2005.She served on the Court of Queen’s Bench of Alberta in Calgary until June 2016 when she was appointed as a judge of the Courts of Appeal of Alberta, the Northwest Territories and Nunavut.Martin is also mother to seven children — proof, she said, that she’s capable of multitasking and resolving disputes.Last year, the Liberal government brought in a new Supreme Court appointment process to encourage more openness and diversity, which also requires justices to be functionally bilingual.In making the appointment, the Prime Minister’s Office underscored Martin’s emphasis on education, equality rights and increasing the number of under-represented groups in the legal world.As a lawyer and academic, Martin was part of a team working on redress for harm experienced by tens of thousands of Indigenous children at residential schools. She said delving into the abuse, isolation and loneliness suffered by the pupils reinforced in her mind the responsibility to learn about the lives of others.Conservative MP Rob Nicholson sought Martin’s views on training for judges on the subject of sexual assault.Martin, who has given presentations on sexual assault laws, said she has “rarely heard a good argument in favour of less education.”But she cautioned that when dealing with the education of judges, it’s important to be mindful of judicial independence and who is chosen to lead a seminar.Martin’s answers revealed a deep thinker with humanity and a broad perspective, said Justice Minister Jody Wilson-Raybould, who attended the session.Martin’s nomination to the Supreme Court ensures the nine-member bench will remain at full strength after Chief Justice Beverley McLachlin retires Dec. 15 after 28 years on the court. The prime minister is expected to name a new chief justice soon.Wilson-Raybould said McLachlin exemplified the qualities a chief justice should have, citing her thorough understanding of the law, ability to foster collegiality among high court judges and leadership as a public representative of the court.— Follow @JimBronskill on Twitterlast_img read more

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How FiveThirtyEight Is Forecasting The 2016 NCAA Tournament

CaliforniaSouth4187186.54.00.7 IndianaEast5193887.45.81.1 BaylorWest5183785.56.01.0 DaytonMidwest7178882.41.60.1 Florida Gulf CoastEast16154471.4<0.1<0.1 North CarolinaEast1207593.943.615.0 VirginiaMidwest1205292.530.49.8 Note, however, that Elo is still just one of six computer rankings that we use for the men’s tournament. The other five are ESPN’s BPI, Jeff Sagarin’s “predictor” ratings, Ken Pomeroy’s ratings, Joel Sokol’s LRMC ratings, and Sonny Moore’s computer power ratings. In addition, we use two human-generated rating systems: the selection committee’s 68-team “S-Curve”, and a composite of preseason ratings from coaches and media polls. The eight systems — six computer-generated and two human-generated — are weighted equally in coming up with a team’s overall rating.We’ve calculated Elo ratings for men’s teams only. For women’s ratings, we rely on the same composite of ratings systems that we used last year. You can find more about the methodology for our women’s forecasts here.As has been the case previously, our ratings are also adjusted for travel distance and (for men’s teams only) player injuries. Our injury adjustment has been slightly improved to account for the higher or lower caliber of replacement players on different teams: Stony Brook, for example, won’t be able to replace a star player as easily as Kentucky can.As a final reminder, these forecasts are probabilistic — something especially important to consider in the men’s tournament this year when there’s about as much parity among teams as we’ve ever seen. In some sense, every team but the UConn women should be thought of as underdogs to win the tournament this year.Check out FiveThirtyEight’s 2016 March Madness Predictions. Michigan StateMidwest2207891.833.98.9 VillanovaSouth2204591.322.46.4 Weber StateEast15162373.3<0.1<0.1 North Carolina-AshevilleSouth15155374.2<0.1<0.1 ConnecticutSouth9187285.32.10.3 Middle TennesseeMidwest15163875.0<0.1<0.1 SouthernWest16139268.0<0.1<0.1 DukeWest4191087.312.11.7 XavierEast2197387.79.91.8 IowaSouth7190485.93.20.6 Arkansas-Little RockMidwest12173478.90.2<0.1 Stephen F. AustinEast14182481.00.4<0.1 KentuckyEast4201490.715.94.4 OregonWest1203388.022.62.6 KansasSouth1209794.545.1%19.1% TexasWest6178884.75.90.9 UtahMidwest3188786.65.30.8 Miami (FL)South3193387.14.91.0 Holy CrossWest16142066.9<0.1<0.1 Texas A&MWest3191586.812.42.4 VanderbiltSouth11184685.62.40.5 MarylandSouth5187687.46.31.3 Fresno StateMidwest14170876.6<0.1<0.1 West VirginiaEast3195689.316.23.4 2016 NCAA Tournament team ratings Wichita StateSouth11189386.62.70.7 Stony BrookEast13166377.10.1<0.1 CincinnatiWest9179483.73.20.3 WisconsinEast7189684.82.90.4 OklahomaWest2197290.032.06.8 HawaiiSouth13173778.0<0.1<0.1 PittsburghEast10178782.31.20.1 Saint Joseph’sWest8181481.61.10.1 ColoradoSouth8175681.50.4<0.1 Northern IowaWest11175180.20.8<0.1 Welcome to FiveThirtyEight’s forecasts of the men’s and women’s NCAA basketball tournaments. We’ve been issuing probabilistic March Madness forecasts in some form since 2011, when FiveThirtyEight was just a couple of us writing for The New York Times. While the basics of the system remain the same, we unveil a couple of new wrinkles each year.Last season, we issued forecasts of the women’s tournament for the first time. Our big change for this year is that we won’t just be updating our forecasts at the end of each game — but also in real time. If a No. 2 seed is losing to a No. 15 seed, you’ll be able to see how that could affect the rest of the bracket, even before the game is over.Live win probabilitiesOur interactive graphic will include a dashboard that shows the score and time remaining in every game as it’s played, as well as the chance that each team will win that game. These probabilities are derived using logistic regression analysis, which lets us plug the current state of a game into a model to produce the probability that either team wins the game. Specifically, we used play-by-play data from the past five seasons of Division I NCAA basketball to fit a model that incorporates:Time remaining in the gameScore differencePre-game win probabilitiesWhich team has possession, with a special adjustment if the team is shooting free throws.These in-game win probabilities won’t account for everything. If a key player has fouled out of a game, for example, his or her team’s win probability is probably a bit lower than we’ve listed. There are also a few places where the model experiences momentary uncertainty: In the handful of seconds between the moment when a player is fouled and the free throws that follow, we use the team’s average free-throw percentage. Still, these probabilities ought to do a reasonably good job of showing which games are competitive and which are in the bag.We built a separate in-game probability model for the women’s tournament that works in exactly the same way but uses historical women’s data. Thus, we’ll be updating our forecasts live for both the men’s and women’s tournament.Excitement indexOur March Madness “excitement index” (loosely based on Brian Burke’s NFL work) is a measure of how much each team’s chances of winning changed over the course of the game and is a good reference for picking the best games to flip to.The calculation is simple: It’s the average change in win probability per basket scored, weighted by the amount of time remaining in the game. This means that a late-game basket has more influence on a game’s rating than a basket near the beginning of the game. We give additional weight to changes in win probability in overtime. Ratings range from 0 to 10, except in extreme cases where they can exceed 10.The index isn’t perfect — this year’s play-in game between Holy Cross and Southern was good, but perhaps not deserving of its 9.4 rating. But even if it doesn’t quite capture the difference between a closely contested slog and a Dunk City run to the Sweet 16, it does a nice job of quantifying how tight a game was and how many big shots were hit.Elo ratingsOtherwise, the methodology for our men’s forecasts is also largely the same as last year. But we’ve developed our own computer rating system — Elo — which we include along with the five computer rankings and two human rankings we used previously.If you’ve followed FiveThirtyEight, you’ll know that we’re big fans of Elo ratings, which we’ve introduced for the NBA, the NFL and other sports. We’ve now applied them for men’s college basketball teams dating back to the 1950s, using game data from ESPN, Sports-Reference.com and other sources.Our methodology for calculating these Elo ratings is highly similar to the one we use for NBA. They rely on relatively simple information — specifically, the final score, home-court advantage, and the location of each game. (College basketball teams perform significantly worse when they travel a long distance to play a game.) They also account for a team’s conference — at the beginning of each season, a team’s Elo rating is regressed toward the mean of other schools in its conference — and whether the game was an NCAA Tournament game. We’ve found that historically, there are actually fewer upsets in the NCAA Tournament than you’d expect from the difference in teams’ Elo ratings, perhaps because the games are played under better and fairer conditions in the tournament than in the regular season. Our Elo ratings account for this and also weight tournament games slightly higher than regular season ones.Elo ratings for the 68 teams to qualify for the men’s tournament follow below. North Carolina-WilmingtonWest13172277.70.2<0.1 YaleWest12179280.21.0<0.1 Cal State BakersfieldWest15163575.00.1<0.1 GonzagaMidwest11191686.03.20.5 TEAMREGIONSEEDELOCOMPOSITEFINAL 4CHAMPS Southern CaliforniaEast8173381.40.2<0.1 IonaMidwest13175978.20.1<0.1 Texas TechMidwest8177781.30.4<0.1 TempleSouth10173078.50.2<0.1 ArizonaSouth6195389.06.01.8 Oregon StateWest7174077.60.2<0.1 Seton HallMidwest6191484.51.80.2 Virginia CommonwealthWest10179883.12.20.2 Fairleigh DickinsonEast16141766.7<0.1<0.1 ChattanoogaEast12161076.6<0.1<0.1 South Dakota StateSouth12173578.60.2<0.1 ButlerMidwest9181584.22.50.3 MichiganEast11176879.60.3<0.1 BuffaloSouth14161375.7<0.1<0.1 PurdueMidwest5193888.713.02.7 Iowa StateMidwest4186786.56.41.0 Austin PeaySouth16147768.8<0.1<0.1 RATINGSPROBABILITY OF… HamptonMidwest16148868.6<0.1<0.1 SyracuseMidwest10177282.71.30.1 ProvidenceEast9182482.50.80.1 TulsaEast11169079.90.2<0.1 Notre DameEast6183284.42.60.3 Green BayWest14166776.20.1<0.1 UPDATE (6:30 p.m. March 18): We’ve updated this post to add information about the excitement index. read more

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Jaguar FType Convertible Hits Indian Market with Starting Price at ₹137 Crore

first_imgJaguar Land Rover, the wholly-owned subsidiary of Tata Motors, launched on Monday its high-end F-Type convertible sports car in India with a starting price of ₹1.37 crore.The two-seater convertible will be released in the Indian market in two variants – the F-Type S and the F-Type V8S. The V6S model packs the 3-litre V6 supercharged petrol engine which churns out a power of 380PS and 460Nm, while the high-end V8S variant is powered by a 5-litre V8 supercharged petrol engine that gives out 495PS and 620Nm. The company claims that V8S reaches 100 km/h in 4.3 seconds and has a top speed of 300 km/h, while the V6S reaches the same speed in 4.9 seconds and claims a top speed of 275 km/h. The F-Type V8S is priced ₹1.61 crore and the VS model goes for ₹1.37 crore.”The Jaguar F-Type is our all-new, two-seater sports car and we believe it will be a game changer for the Indian sports car market. With its stunning design and driver focused engineering, this car will further enhance the appeal of our brand and I am confident that it will arouse senses and stir emotions like no other car in India,” said Rohit Suri, vice-president, Jaguar Land Rover India.The car which was first unveiled at the Paris Auto Show 2012 had bagged the title of 2013 World Car Design of the Year. The F-Type is the successor of Jaguar’s E-Type model. The vehicle will be pitted against Porsche Cayman and Boxster. According to the company, the Indian arm of Jaguar witnessed a 68 percent growth in sales in the first quarter of the year.last_img read more

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Study provides surprisingly complex portrait of ancient trade networks

first_img Journal information: Proceedings of the National Academy of Sciences This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only. Explore further More information: Compositional data supports decentralized model of production and circulation of artifacts in the pre-Columbian south-central Andes. PNAS 2017 114 (20) E3917-E3926; published ahead of print May 1, 2017, DOI: 10.1073/pnas.1610494114AbstractThe circulation and exchange of goods and resources at various scales have long been considered central to the understanding of complex societies, and the Andes have provided a fertile ground for investigating this process. However, long-standing archaeological emphasis on typological analysis, although helpful to hypothesize the direction of contacts, has left important aspects of ancient exchange open to speculation. To improve understanding of ancient exchange practices and their potential role in structuring alliances, we examine material exchanges in northwest Argentina (part of the south-central Andes) during 400 BC to AD 1000 (part of the regional Formative Period), with a multianalytical approach (petrography, instrumental neutron activation analysis, laser ablation inductively coupled plasma mass spectrometry) to artifacts previously studied separately. We assess the standard centralized model of interaction vs. a decentralized model through the largest provenance database available to date in the region. The results show: (i) intervalley heterogeneity of clays and fabrics for ordinary wares; (ii) intervalley homogeneity of clays and fabrics for a wide range of decorated wares (e.g., painted Ciénaga); (iii) selective circulation of two distinct polychrome wares (Vaquerías and Condorhuasi); (iv) generalized access to obsidian from one major source and various minor sources; and (v) selective circulation of volcanic rock tools from a single source. These trends reflect the multiple and conflicting demands experienced by people in small-scale societies, which may be difficult to capitalize by aspiring elites. The study undermines centralized narratives of exchange for this period, offering a new platform for understanding ancient exchange based on actual material transfers, both in the Andes and beyond. The study challenges existing centralized network models of interaction in favor of a decentralized network structure. The researchers built the largest provenance database ever constructed for the region, taking a multianalytical approach that considered lithic sources, pottery analysis, and comparisons of clays and fabrics. These materials and artifacts had previously only been studied separately. The wide-ranging collection of data resulted in a complex, sprawling portrait of northwest Argentina during the Formative Period.This era was characterized by the slow development of sedentary societies with subsistence and crafting technologies. In older studies, researchers reconstructed regional networks based on typological similarities between materials and artifacts. The new study attempts to investigate interactions between both local and regional networks in the Andes during this period by comparing the manufacture and sources of materials, as opposed only to looking at styles.For instance, an examination of obsidian artifacts demonstrated that they shared a common source. But the differences between the cultural styles and assemblages demonstrated that many groups from different communities and cultures shared access to the same source. This allowed the researchers to create a regional network representing the movement and propagation of this source of rock.The petrography analysis of ceramics sources revealed a variety of technical production modes. The researchers found distinct chemical fingerprints for ceramic artifacts found in specific valleys and areas. “This pattern strongly suggests that there was a set of middle-range distance connections involving not only the circulation of raw materials and artifacts, but also the transmission of skills and concepts of manufacture and design that were not exclusionary,” the authors note.Notably, the study did not find characteristic artifacts from the Ambato Valley—these are distinctive gray-black wares found in past archaeological excavations that did not seem to spread among the regions encompassed by the current study. This calls into question the presumed centrality of the Ambato Valley as a node within the regional trade network. “Together with the observed low frequency of painted Aguado varieties in our core study area, the results of the geochemical analysis support a reconsideration of the purported central role of this valley,” the researchers write.The study concludes that the area supported many circulation networks involving multiple means of transport, including the presumed use of llamas. Additionally, local networks of different types were incorporated into larger regional networks that best served the needs of communities during that period–needs that were not necessarily dictated by either socio-political considerations or the desires of cultural elites. “Focusing on close intercommunity links rooted on common craft practices rather than solely on stylistic reconstructions is a more fruitful avenue to explore the ancient circulation of goods, skills, and people without assuming the capacity of early elites to manipulate and capitalize on such networks,” the authors conclude. © 2017 Phys.orgcenter_img (Phys.org)—The study of ancient civilizations, particularly those that did not leave extensive writing in the archaeological record, is reliant on the evidence of other kinds of material artifacts. And one of the keys to understanding large, complex societies is mapping the circulation of such artifacts. An international research collaborative recently published a study in the Proceedings of the National Academy of Sciences on the production and circulation of artifacts in the south-central Andes during 400 BC to 1000 AD. Albania stops smugglers of 230 ancient Apollonia artifacts Distribution routes for obsidian sources, decorated MG2 and MG7 pottery wares, Vaquerías and Condorhuasi wares, and type 1 vulcanite. Credit: (c) PNAS 2017 114 (20) E3917-E3926; published ahead of print May 1, 2017, doi:10.1073/pnas.1610494114 Citation: Study provides surprisingly complex portrait of ancient trade networks (2017, May 23) retrieved 18 August 2019 from https://phys.org/news/2017-05-surprisingly-complex-portrait-ancient-networks.htmllast_img read more

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