Accelerating Acceptance 2016

Non-LGBT Americans are increasingly accepting of LGBT people, but many don't realize what battles remain to be fought for full equality, a new GLAAD report indicates. GLAAD's second annual Accelerating Acceptance report, based on information gathered for the organization by the Harris Poll last fall, found that respondents' comfort level with LGBT people rose since the previous year.But many participants in the survey were unaware of the challenges still facing LGBT Americans. Half of non-LGBT respondents thought LGBT people had "the same rights as anybody else," as the survey put it, when actually 31 states have no law preventing a person from being fired or denied housing simply for being LGBT. The assumption that LGBT people have equal rights across the board may be due to the widespread publicity about last year's Supreme Court marriage equality ruling, GLAAD officials said.A significant minority of non-LGBT respondents -- 27 percent -- thought violence against transgender people was not a serious problem, even though at least 21 trans women, most of them women of color, were murdered in the U.S. in 2015. Also, 37 percent said homelessness among LGBT youth was not a major issue, when in reality an estimated 40 percent of homeless young people identify as LGBT. And a third of non-LGBT respondents, including some allies, said they had no strong opinion about LGBT issues.The 2015 survey was conducted online October 5-7 among 2,032 Americans age 18 and older. The non-LGBT sub-sample was 1,781. The previous survey was conducted in November 2014 and involved 2,010 American adults, 1,821 of them non-LGBT

Acceptance practice

Acceptances

Acceptance of Health Information System for Public Health Centre in North Borneo, Indonesia

This study sought the factor associated with own acceptance of HIS for PHC by using the modification of Technology Acceptance Model (TAM) in the Sebengkok PHC, Central Tarakan Subdistrict, Tarakan City, North Borneo, Indonesia. A cross-sectional approach was conducted through a survey on the 37 of PHC\u27s user. A set of questionnaires which was adopted from the previous research was used to collect the information from the participant. The model was developed by involving job relevance, output quality, result demonstrability, screen design, terminology, facilitating condition, perceived of usefulness, perceived ease of use, intention to use and system use (actual usage) as the construct. According to the hypothesis testing, perceived usefulness predicted by terminology, perceived ease of use is significantly predicted by screen design and terminology, perceived usefulness significantly predicts the intention of use and perceived ease of use, while system use which predicted considerably by the intention of use and facilitating condition. This study may have a contribution to the future improvement of HIS for PHC and guide the next coming research to dig the difference acceptance among the user

Numerical Representations of Acceptance

Accepting a proposition means that our confidence in this proposition is strictly greater than the confidence in its negation. This paper investigates the subclass of uncertainty measures, expressing confidence, that capture the idea of acceptance, what we call acceptance functions. Due to the monotonicity property of confidence measures, the acceptance of a proposition entails the acceptance of any of its logical consequences. In agreement with the idea that a belief set (in the sense of Gardenfors) must be closed under logical consequence, it is also required that the separate acceptance o two propositions entail the acceptance of their conjunction. Necessity (and possibility) measures agree with this view of acceptance while probability and belief functions generally do not. General properties of acceptance functions are estabilished. The motivation behind this work is the investigation of a setting for belief revision more general than the one proposed by Alchourron, Gardenfors and Makinson, in connection with the notion of conditioning.Comment: Appears in Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence (UAI1995

Vice Presidential Acceptance Speech

Copyright Fordham University School of Law. All Rights Reserved.https://ir.lawnet.fordham.edu/vice_presidential_campaign_materials_1984/1013/thumbnail.jp

Spreading Acceptance through Performance

When Tricia Castañeda-Gonzales ’09 returned to the Linfield stage this year, she brought Latino heritage to life through rhythmic bilingual expression

Delayed acceptance ABC-SMC

Approximate Bayesian computation (ABC) is now an established technique for statistical inference used in cases where the likelihood function is computationally expensive or not available. It relies on the use of a~model that is specified in the form of a~simulator, and approximates the likelihood at a~parameter value $\theta$ by simulating auxiliary data sets $x$ and evaluating the distance of $x$ from the true data $y$. However, ABC is not computationally feasible in cases where using the simulator for each $\theta$ is very expensive. This paper investigates this situation in cases where a~cheap, but approximate, simulator is available. The approach is to employ delayed acceptance Markov chain Monte Carlo (MCMC) within an ABC sequential Monte Carlo (SMC) sampler in order to, in a~first stage of the kernel, use the cheap simulator to rule out parts of the parameter space that are not worth exploring, so that the ``true'' simulator is only run (in the second stage of the kernel) where there is a~reasonable chance of accepting proposed values of $\theta$. We show that this approach can be used quite automatically, with few tuning parameters. Applications to stochastic differential equation models and latent doubly intractable distributions are presented