BS Summary: This article contains 14 faulty reasoning types, including Hasty Generalization, Appeal to Emotion, and Unattributed Quote, with Optimism Bias as the most egregious example at 22.8% saturation with 105 hits. Analysis detected 523 faulty-reasoning hits from 461 analyzed words, generating a BS Score of 39.2% and a BS Rank of 29% (15,691 of 21,887 articles). This article is better (less manipulative) than 71.70% of the article peer group.

More formerly incarcerated Hoosiers could soon get job training and credentials through new federal funding. 
The U.S. 
Department of Labor awarded two grants each worth $5.1 million to the Indiana Department of Workforce Development and Keys2Work, RecycleForce and 2nd Chance Indiana. 
The federal RESTART grants  which stands for Reentry Employment in Skilled Trades, Advanced Manufacturing, Registered Apprenticeships, and Training  will fund the agency’s and nonprofits’ efforts to provide training in skilled trades for people being released from prison or jail. 
Indianapolis-based nonprofit Keys2Work is working with its sister organization RecycleForce , as well as 2nd Chance Indiana, to train formerly incarcerated people between the ages of 18 and 24. 
That program, which Keys2Work is calling “Developing the Work Muscle,” will provide training to 680 people over three years in seven counties, including Marion County. 
RecycleForce will provide employment in Indianapolis, and 2nd Chance Indiana will work in Tipton, Howard, Kosciusko, Dekalb, Elkhart and Noble counties. 
“We’re going to show you how to work by asking you to work and giving you the grace to fail and to try again,” said Gina Davis , Keys2Work’s senior director, “in an environment where they are surrounded by peers and peer leaders who have been on the same journeys they are on.” 
In Indianapolis, RecycleForce provides transitional employment, meaning short-term paid work that’s designed to help people reentering society get the experience and skills needed for the workplace. 
The nonprofit uses what’s called the “ABC” model  any job, better job, career. 
“We have individuals that start in the ‘any’ job, but we’re able to place them in the better job with Keys2Work,” said Tiana Johnson, RecycleForce’s chief operating officer. 
Through Keys2Work, employees can also get credentials , from entry-level safety certifications to hazardous waste management training. 
While program length is flexible for each participant, most workers will spend about three months in transitional employment before moving on to another job or getting further training, Davis said. 
“We give people their full time, their full opportunity to spend as much time here as they want,” Davis said. 
“It’s very important that we’re always customizing a person’s experience based upon their needs.” 
Keys2Work plans to start enrolling workers  mostly through referrals from the Indiana Department of Corrections  before Oct. 
1. 
While Keys2Work’s grant will provide training to young people, the Indiana Department of Workforce Development’s funding will support training, employment and apprenticeship opportunities for formerly incarcerated adults aged 25 and older. 
The majority of the state’s grant  about $4.3 million  will be distributed to local workforce boards throughout Indiana, which will in turn run training programs and supportive services. 
In Indianapolis and Marion County, the workforce board is EmployIndy . 
Article reasoning-pattern comparisonThis article: 5.6%Claire Rafford: 0.6%Mirror Indy: 1.3%Confirmation Bias5.6%This article: 4.1%Claire Rafford: 1.0%Mirror Indy: 0.1%Anchoring Bias4.1%This article: 6.5%Claire Rafford: 1.0%Mirror Indy: 2.1%Availability Heuristic6.5%This article: 5.4%Claire Rafford: 1.4%Mirror Indy: 0.7%Representativeness Heuristic5.4%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.2%Hindsight Bias0.0%This article: 6.5%Claire Rafford: 1.4%Mirror Indy: 0.5%Overconfidence Bias6.5%This article: 0.0%Claire Rafford: 2.3%Mirror Indy: 3.4%Framing Effect0.0%This article: 0.0%Claire Rafford: 0.2%Mirror Indy: 0.7%Loss Aversion0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.2%Status Quo Bias0.0%This article: 0.0%Claire Rafford: 0.4%Mirror Indy: 0.2%Sunk Cost Effect0.0%This article: 22.8%Claire Rafford: 8.7%Mirror Indy: 3.3%Optimism Bias22.8%This article: 0.0%Claire Rafford: 4.2%Mirror Indy: 1.1%Pessimism Bias0.0%This article: 0.0%Claire Rafford: 4.0%Mirror Indy: 5.9%Negativity Bias0.0%This article: 6.1%Claire Rafford: 1.7%Mirror Indy: 1.2%Self-Serving Bias6.1%This article: 0.0%Claire Rafford: 0.4%Mirror Indy: 0.9%Fundamental Attribution Error0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.1%Actor-Observer Bias0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 1.5%In-Group Bias0.0%This article: 0.0%Claire Rafford: 0.5%Mirror Indy: 0.1%Out-Group Homogeneity Bias0.0%This article: 6.1%Claire Rafford: 0.6%Mirror Indy: 1.9%Halo Effect6.1%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.0%Horn Effect0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Claire Rafford: 0.7%Mirror Indy: 0.4%Recency Bias0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.3%Primacy Effect0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.1%Blind-Spot Bias0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.2%Ad Hominem0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.0%Straw Man0.0%This article: 8.9%Claire Rafford: 2.6%Mirror Indy: 2.4%Appeal to Authority8.9%This article: 0.0%Claire Rafford: 0.5%Mirror Indy: 0.7%False Dilemma0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.3%Slippery Slope0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.0%Circular Reasoning0.0%This article: 12.6%Claire Rafford: 1.3%Mirror Indy: 3.7%Hasty Generalization12.6%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.0%Red Herring0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.1%Bandwagon0.0%This article: 11.5%Claire Rafford: 3.4%Mirror Indy: 2.2%Appeal to Emotion11.5%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.1%Begging the Question0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 1.0%Post Hoc (False Cause)0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.1%Tu Quoque0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.3%Burden of Proof0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.1%Appeal to Nature0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.2%Composition/Division0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 4.1%Anecdotal0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.1%No True Scotsman0.0%This article: 0.7%Claire Rafford: 0.1%Mirror Indy: 0.5%Ambiguity (Equivocation)0.7%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.0%Middle Ground0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.0%Personal Incredulity0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.0%Special Pleading0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.0%Genetic Fallacy0.0%This article: 11.5%Claire Rafford: 1.9%Mirror Indy: 0.7%Unattributed Quote11.5%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.2%Quote-first Misdirection0.0%This article: 5.2%Claire Rafford: 0.5%Mirror Indy: 3.4%Biased Writer Voice5.2%This article: 0.0%Claire Rafford: 0.3%Mirror Indy: 0.7%Indoctrination0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.6%Politically Left Leaning Bias0.0%This article: 0.0%Claire Rafford: 0.0%Mirror Indy: 0.0%Politically Right Leaning Bias0.0%This article: 0.0%Claire Rafford: 1.1%Mirror Indy: 1.8%Attempt to Sell a Product or S…0.0%

461 words analyzed.

Speakers

4speakers31%attributed speech319writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 10 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 2 words • 0.0% coverageWriter's voice • 24 words • 100.0% coverageWriter's voice • 41 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageGina Davis • 53 words • 100.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageTiana Johnson • 28 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageDavis • 30 words • 0.0% coverageDavis • 20 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 1 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageEmployIndy • 11 words • 0.0% coverage
Selected voice

Gina Davis

100%flagged-word coverage
53 attributed words37% of attributed speech71% writer coverage
0%50.0%100.0%Unattributed Quote+100.0 ptsWriter: 0.0%Gina Davis: 100.0%100.0%Biased Writer Voice-7.5 ptsWriter: 7.5%Gina Davis: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.