A poll of 1,098 Honolulu voters found:
- Cayetano led the mayoral race with 51% support, followed by Caldwell at 24% and Carlisle at 19%.
- 61% of voters decided who to support over a month ago. Cayetano had the most long-term support at 66% of his voters.
- Support for rail was lower at 39% compared to 55% who oppose it, with the largest opposition groups being Carlisle and Caldwell supporters.
Mark McCrindle Australian Communities Forum: Communities DefinedMark McCrindle
Mark McCrindle of McCrindle Research presented this at The Australian Communities Forum in November 2012 in Sydney. It outlines 5 key demographic shifts occurring in Australia, a demographic snapshot of what Australia would look like if it were 100 households, and 8 key factors around how communities operate.
European Hematology Association Annual Congress 2011: Patient Advocacy Session on "Adherence:Are You Sure your Patients Are taking Their Medicines?", presented by Giora Sharf, Co-founder, CML Advocates Network
Lane County Prevention Program Focus Group reportsLane Prevention
Health Policy Research Northwest, commissioned by Lane County Health & Human Services, conducted focus group reports in 2011 to determine community perceptions and awareness of 2) youth gambling and 2) the Prevention Program itself.
Mark McCrindle Australian Communities Forum: Communities DefinedMark McCrindle
Mark McCrindle of McCrindle Research presented this at The Australian Communities Forum in November 2012 in Sydney. It outlines 5 key demographic shifts occurring in Australia, a demographic snapshot of what Australia would look like if it were 100 households, and 8 key factors around how communities operate.
European Hematology Association Annual Congress 2011: Patient Advocacy Session on "Adherence:Are You Sure your Patients Are taking Their Medicines?", presented by Giora Sharf, Co-founder, CML Advocates Network
Lane County Prevention Program Focus Group reportsLane Prevention
Health Policy Research Northwest, commissioned by Lane County Health & Human Services, conducted focus group reports in 2011 to determine community perceptions and awareness of 2) youth gambling and 2) the Prevention Program itself.
Kharfen: DC HIV Public-Private Partnershipshealthhiv
Michael Kharfen
Bureau Chief, Partnerships, Capacity Building, Community Outreach
DC Department of Health
HIV/AIDS, Hepatitis, STD and TB Administration
Gov. Ige sent a letter to California Congresswoman Anna Eshoo in response to her August 2020 request for information about Hawaii's pandemic response.
https://www.civilbeat.org/2020/08/california-congresswoman-wants-answers-on-hawaiis-virus-response-effort/
Audit of the Department of the Honolulu Prosecuting Attorney’s Policies, Proc...Honolulu Civil Beat
This audit was conducted pursuant to Resolution 19-255,
requesting the city auditor to conduct a performance audit of the Honolulu Police Department and the Department of the Prosecuting Attorney’s policies and procedures related to employee misconduct.
Audit of the Honolulu Police Department’s Policies, Procedures, and ControlsHonolulu Civil Beat
The audit objectives were to:
1. Evaluate the effectiveness of HPD’s existing policies, procedures, and controls to identify and respond to complaints or incidents concerning misconduct, retaliation, favoritism, and abuses of power by its management and employees;
2. Evaluate the effectiveness of HPD's management control environment and practices to correct errors and prevent any misconduct, retaliation, favoritism, and abuses of power by its
management and employees; and
3. Make recommendations to improve HPD’s policies, procedures, and controls to minimize and avoid future managerial and operational breakdowns caused by similar misconduct.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptx
Civil Beat Poll August 2012 Honolulu Mayor Results
1. Honolulu Mayor 1
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Vote_Screen
Already voted 29%
Definitely voting 70%
Might vote 1%
Total 100%
Mayor
Cayetano 51%
Carlisle 19%
Caldwell 24%
None 1%
Unsure 4%
Total 100%
Mayor_Decide
Two weeks 18%
Past month 20%
Month+ 61%
Unsure 1%
Total 100%
2. Honolulu Mayor 2
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
(Cayetano Supporters Only: Sample Size = 561; Margin of Error +/- 4.1%)
Cayetano_Second
Carlisle 24%
Caldwell 23%
Neither 47%
Unsure 6%
Total 100%
(Carlisle Supporters Only: Sample Size = 210; Margin of Error +/- 6.8%)
Carlisle_Second
Cayetano 7%
Caldwell 70%
Neither 19%
Unsure 3%
Total 100%
(Caldwell Supporters Only: Sample Size = 263; Margin of Error +/- 6.0%)
Caldwell_Second
Cayetano 12%
Carlisle 66%
Neither 15%
Unsure 7%
Total 100%
Rail
Support 39%
Oppose 55%
Unsure 6%
Total 100%
3. Honolulu Mayor 3
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Ads
A lot 22%
A little 37%
None 37%
Unsure 4%
Total 100%
Debates
A lot 40%
A little 33%
None 23%
Unsure 4%
Total 100%
News
A lot 42%
A little 37%
None 17%
Unsure 4%
Total 100%
Endorsements
A lot 10%
A little 28%
None 58%
Unsure 4%
Total 100%
Own_Research
A lot 58%
A little 28%
None 9%
Unsure 5%
Total 100%
4. Honolulu Mayor 4
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
5. Honolulu Mayor 5
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Obama
Approve strongly 45%
Approve somewhat 20%
Disapprove somewhat 13%
Disapprove strongly 20%
Unsure 2%
Total 100%
Obama_Condensed
Approve 65%
Disapprove 33%
Unsure 2%
Total 100%
6. Honolulu Mayor 6
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Gender
Male 46%
Female 54%
Total 100%
Age
18-29 4%
30-39 5%
40-49 12%
50-64 37%
65+ 42%
Total 100%
Ethnicity
Caucasian 37%
Japanese 22%
Filipino 8%
Hawaiian 10%
Chinese 9%
Hispanic/Latino 1%
Other/Mixed 13%
Total 100%
Politics
Liberal/Progressive 21%
Moderate 40%
Conservative 25%
Unsure 14%
Total 100%
Party
Democrat 47%
Republican 19%
Independent 27%
Unsure 7%
7. Honolulu Mayor 7
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Total 100%
8. Honolulu Mayor 8
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Education
No degree 3%
High School Degree 25%
College Degree 41%
Graduate Degree 31%
Total 100%
Religion
Catholic 27%
Evangelical 11%
Mormon 2%
Other Christian 23%
Buddhist 10%
Other 5%
None 20%
Total 100%
Military_Family
Yes 14%
No 86%
Total 100%
Union_Househod
Yes 31%
No 69%
Total 100%
9. Honolulu Mayor 9
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Relationship_Status
Married 63%
Civil Partnership 4%
Single 13%
Divorced/Separated 10%
Widowed 11%
Total 100%
Income_Household
$50,000 or less 31%
$50,000-$100,000 40%
$100,000 or more 29%
Total 100%
County_CD
Oahu 1 71%
Oahu 2 29%
Total 100%
10. Honolulu Mayor 10
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Mayor * Vote_Screen Crosstabulation
% within Vote_Screen
Vote_Screen
Already Definitely
voted voting Might vote
Mayor Cayetano 50% 51% 69%
Carlisle 22% 18% 13%
Caldwell 25% 24%
None 2% 1% 6%
Unsure 3% 5% 13%
Total 100% 100% 100%
Mayor * Mayor_Decide Crosstabulation
% within Mayor_Decide
Mayor_Decide
Two weeks Past month Month+ Unsure
Mayor Cayetano 45% 50% 58% 71%
Carlisle 25% 20% 19% 14%
Caldwell 30% 29% 23% 14%
Total 100% 100% 100% 100%
Mayor_Decide * Mayor Crosstabulation
% within Mayor
Mayor
Cayetano Carlisle Caldwell
Mayor_Decide Two weeks 14% 22% 21%
Past month 19% 20% 24%
Month+ 66% 57% 55%
Unsure 1% 0% 0%
Total 100% 100% 100%
11. Honolulu Mayor 11
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Mayor * Rail Crosstabulation
% within Rail
Rail
Support Oppose Unsure
Mayor Cayetano 7% 85% 27%
Carlisle 41% 4% 8%
Caldwell 48% 6% 30%
None 1% 1% 6%
Unsure 3% 3% 29%
Total 100% 100% 100%
Rail * Mayor Crosstabulation
% within Mayor
Mayor
Cayetano Carlisle Caldwell None Unsure
Rail Support 5% 85% 78% 25% 27%
Oppose 92% 12% 14% 50% 35%
Unsure 3% 2% 7% 25% 38%
Total 100% 100% 100% 100% 100%
12. Honolulu Mayor 12
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Mayor * Ads Crosstabulation
% within Ads
Ads
A lot A little None Unsure
Mayor Cayetano 48% 46% 59% 39%
Carlisle 25% 21% 14% 13%
Caldwell 24% 28% 21% 13%
None 0% 1% 1% 11%
Unsure 4% 4% 4% 24%
Total 100% 100% 100% 100%
Mayor * Debates Crosstabulation
% within Debates
Debates
A lot A little None Unsure Total
Mayor Cayetano 52% 51% 52% 37% 51%
Carlisle 20% 17% 22% 17% 19%
Caldwell 26% 27% 19% 9% 24%
None 1% 2% 0% 9% 1%
Unsure 2% 3% 6% 28% 4%
Total 100% 100% 100% 100% 100%
Mayor * News Crosstabulation
% within News
News
A lot A little None Unsure
Mayor Cayetano 47% 54% 57% 35%
Carlisle 21% 18% 19% 9%
Caldwell 29% 22% 19% 12%
None 1% 2% 1% 9%
Unsure 2% 4% 4% 35%
Total 100% 100% 100% 100%
13. Honolulu Mayor 13
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Mayor * Endorsements Crosstabulation
% within Endorsements
Endorsements
A lot A little None Unsure
Mayor Cayetano 41% 37% 60% 36%
Carlisle 18% 22% 18% 7%
Caldwell 35% 33% 18% 16%
None 1% 2% 1% 11%
Unsure 4% 5% 2% 30%
Total 100% 100% 100% 100%
Mayor * Own_Research Crosstabulation
% within Own_Research
Own_Research
A lot A little None Unsure
Mayor Cayetano 56% 45% 45% 38%
Carlisle 17% 22% 28% 15%
Caldwell 24% 28% 19% 11%
None 1% 1% 3% 2%
Unsure 2% 4% 6% 34%
Total 100% 100% 100% 100%
14. Honolulu Mayor 14
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Mayor * Obama Crosstabulation
% within Obama
Obama
Approve Approve Disapprove Disapprove
strongly somewhat somewhat strongly Unsure
Mayor Cayetano 39% 48% 64% 73% 40%
Carlisle 23% 16% 19% 16% 4%
Caldwell 35% 25% 15% 5% 12%
None 2% 2% 1% 1% 4%
Unsure 1% 8% 2% 5% 40%
Total 100% 100% 100% 100% 100%
Obama * Mayor Crosstabulation
% within Mayor
Mayor
Cayetano Carlisle Caldwell None Unsure
Obama Approve strongly 34% 53% 66% 50% 15%
Approve somewhat 19% 17% 21% 25% 38%
Disapprove somewhat 16% 13% 8% 6% 6%
Disapprove strongly 29% 17% 5% 13% 21%
Unsure 2% 0% 1% 6% 21%
Total 100% 100% 100% 100% 100%
15. Honolulu Mayor 15
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Mayor * Obama_Condensed Crosstabulation
% within Obama_Condensed
Obama_Condensed
Approve Disapprove Unsure
Mayor Cayetano 42% 70% 40%
Carlisle 21% 17% 4%
Caldwell 32% 9% 12%
None 2% 1% 4%
Unsure 4% 4% 40%
Total 100% 100% 100%
Obama_Condensed * Mayor Crosstabulation
% within Mayor
Mayor
Cayetano Carlisle Caldwell None Unsure
Obama_Condensed Approve 53% 70% 86% 75% 52%
Disapprove 45% 30% 13% 19% 27%
Unsure 2% 0% 1% 6% 21%
Total 100% 100% 100% 100% 100%
16. Honolulu Mayor 16
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Mayor * Gender Crosstabulation
% within Gender
Gender
Male Female
Mayor Cayetano 51% 51%
Carlisle 20% 18%
Caldwell 23% 25%
None 2% 1%
Unsure 4% 4%
Total 100% 100%
Mayor * Age Crosstabulation
% within Age
Age
18-29 30-39 40-49 50-64 65+
Mayor Cayetano 33% 46% 55% 49% 54%
Carlisle 25% 16% 20% 20% 18%
Caldwell 28% 26% 18% 27% 23%
None 4% 2% 1% 2%
Unsure 15% 8% 5% 4% 3%
Total 100% 100% 100% 100% 100%
Mayor * Politics Crosstabulation
% within Politics
Politics
Liberal/Progressive Moderate Conservative Unsure
Mayor Cayetano 39% 50% 67% 44%
Carlisle 21% 17% 17% 22%
Caldwell 36% 28% 10% 22%
None 0% 1% 2% 4%
Unsure 3% 4% 4% 8%
Total 100% 100% 100% 100%
17. Honolulu Mayor 17
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Mayor * Party Crosstabulation
% within Party
Party
Democrat Republican Independent Unsure
Mayor Cayetano 40% 62% 62% 49%
Carlisle 21% 22% 14% 13%
Caldwell 33% 12% 19% 20%
None 1% 2% 1% 3%
Unsure 4% 3% 4% 16%
Total 100% 100% 100% 100%
Party * Mayor Crosstabulation
% within Mayor
Mayor
Cayetano Carlisle Caldwell None Unsure
Party Democrat 38% 54% 65% 44% 39%
Republican 23% 22% 9% 25% 11%
Independent 34% 20% 21% 19% 26%
Unsure 6% 5% 5% 13% 24%
Total 100% 100% 100% 100% 100%
Mayor * Education Crosstabulation
% within Education
Education
High
School College Graduate
No degree Degree Degree Degree
Mayor Cayetano 31% 56% 50% 52%
Carlisle 10% 20% 19% 17%
Caldwell 31% 19% 25% 28%
None 7% 2% 2% 0%
Unsure 21% 3% 4% 3%
Total 100% 100% 100% 100%
18. Honolulu Mayor 18
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Mayor * Ethnicity Crosstabulation
% within Ethnicity
Ethnicity
Hispanic/ Other/
Caucasian Japanese Filipino Hawaiian Chinese Latino Mixed
Mayor Cayetano 56% 46% 53% 51% 41% 75% 48%
Carlisle 23% 12% 21% 12% 17% 13% 24%
Caldwell 18% 34% 18% 31% 32% 13% 21%
None 0% 2% 3% 4% 1% 2%
Unsure 3% 6% 4% 1% 9% 6%
Total 100% 100% 100% 100% 100% 100% 100%
Mayor * Religion Crosstabulation
% within Religion
Religion
Other
Catholic Evangelical Mormon Christian Buddhist Other None
Mayor Cayetano 55% 47% 46% 52% 52% 55% 46%
Carlisle 20% 25% 19% 16% 10% 14% 21%
Caldwell 21% 20% 31% 28% 29% 25% 26%
None 2% 1% 5% 2% 1%
Unsure 1% 8% 4% 4% 5% 4% 7%
Total 100% 100% 100% 100% 100% 100% 100%
19. Honolulu Mayor 19
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Mayor * Military_Family Crosstabulation
% within Military_Family
Military_Family
Yes No
Mayor Cayetano 53% 51%
Carlisle 16% 19%
Caldwell 21% 25%
None 3% 1%
Unsure 7% 4%
Total 100% 100%
Mayor * Union_Househod Crosstabulation
% within Union_Househod
Union_Househod
Yes No
Mayor Cayetano 46% 53%
Carlisle 17% 19%
Caldwell 32% 22%
None 2% 1%
Unsure 3% 5%
Total 100% 100%
Mayor * Relationship_Status Crosstabulation
% within Relationship_Status
Relationship_Status
Civil
Married Partnership Single Divorced/Separated Widowed
Mayor Cayetano 52% 62% 42% 51% 50%
Carlisle 19% 27% 15% 16% 21%
Caldwell 25% 5% 31% 31% 19%
None 0% 4% 1% 5%
Unsure 4% 5% 9% 1% 5%
Total 100% 100% 100% 100% 100%
20. Honolulu Mayor 20
July 31 – August 2, 2012
Sample Size = 1,098; Margin of Error +/- 3.0%
Mayor * Income_Household Crosstabulation
% within Income_Household
Income_Household
$50,000 or $50,000- $100,000
less $100,000 or more
Mayor Cayetano 51% 52% 46%
Carlisle 16% 19% 21%
Caldwell 21% 25% 32%
None 3% 1%
Unsure 8% 3% 1%
Total 100% 100% 100%
Mayor * County_CD Crosstabulation
% within County_CD
County_CD
Oahu 1 Oahu 2
Mayor Cayetano 51% 52%
Carlisle 18% 23%
Caldwell 26% 19%
None 2% 1%
Unsure 4% 5%
Total 100% 100%