Aussie reveals Indians only hiring Indians at federal agency ⁠80%

By The Noticer⁠93%

8/1/2026, 4:06:15 AM

BS Summary: This article contains 24 faulty reasoning types, including Negativity Bias, Availability Heuristic, and Hasty Generalization, with Anecdotal as the most egregious example at 40.5% saturation with 208 hits. Analysis detected 1,443 faulty-reasoning hits from 513 analyzed words, generating a BS Score of 65.6% and a BS Rank of ⁠80% (5,276 of 25,563 articles). This article is worse (more manipulative) than 79.40% of the article peer group.

An Australian public servant has revealed that Indian managers at a federal agency are only hiring other Indians, sparking a flood of similar complaints. 
The Public Service worker said in a post on Reddit this week that they were pro-diversity, but that Indians dominating hiring was having the opposite effect. 
“I really don’t want to sound racist but I’m currently working for a federal agency,” the post read. 
“Over the last year our team of analysts got broken into silos and every manager of those silos is now Indian. 
Since then, the only new hires have been Indian from every single silo. 
“I really have nothing against people that are not of my ethnicity, but previously we had complete diversity in the new hires in our team, from all over the world. 
East Asian, European (as in someone born in Europe, not white Australian), central Asian and South American. 
“I know this sounds like crackpot One Nation nonsense, and I’m a big believer in diversity but this is really not feeling very diverse.” 
The post has since been censored but generated hundreds of responses before it was removed, with many other Aussies saying they had experienced the same thing at their own workplaces. 
“I work in a federal government department and there is a team of seven Indian women, which is managed by an Indian woman. 
The odds of all these Indian women being the most suitable for the job over all other candidates is impossibly high, but nobody can say anything,” one comment read. 
“I have spent many years in supermarkets and have experienced the same issue happening there. 
Once there is an Indian department manager they almost exclusively hire only other Indians,” said another. 
“Having to do the mandatory learning every six months about how we should be inclusive to all cultures in the work force, and then you sit down to lunch with your colleagues and they all speak in Hindi so you can’t even participate in conversation is one memory from working in tech at a bank that I won’t forget,” another wrote. 
“Stuff like this puts One Nation in power. 
Our government should never have accepted the number of migrants from one country that they did.” 
But some argued that Indians were underrepresented in upper management, or claimed the phenomenon was not due to in-group hiring but caused by high turnover and large numbers of Indian applicants. 
“To be honest: every agency that I’ve worked at in the past few years with a heavy “service delivery” focus — such as Services Australia — had a predominantly Indian staff,” a public service worker wrote. 
“My understanding is that the IT-focused agencies are similar. 
From my perspective, tons of Indian people are applying for these jobs (which are largely entry level), and once inside the agency are encouraging their family members to apply. 
“I don’t think there are any Indian hiring managers hiring exclusively Indian staff, it’s purely a sheer weight of numbers thing with the applications.” 
Header image credit: Pexels. 
Article reasoning-pattern comparisonThis article: 10.7%The Noticer: 8.5%CNN Politics: 5.2%Confirmation Bias10.7%This article: 1.8%The Noticer: 0.4%CNN Politics: 0.7%Anchoring Bias1.8%This article: 33.1%The Noticer: 16.3%CNN Politics: 5.5%Availability Heuristic33.1%This article: 14.0%The Noticer: 5.8%CNN Politics: 1.8%Representativeness Heuristic14.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.2%Hindsight Bias0.0%This article: 5.7%The Noticer: 2.8%CNN Politics: 1.0%Overconfidence Bias5.7%This article: 0.0%The Noticer: 1.6%CNN Politics: 10.2%Framing Effect0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.8%Loss Aversion0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.3%Status Quo Bias0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.0%Sunk Cost Effect0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.2%Optimism Bias0.0%This article: 7.8%The Noticer: 1.9%CNN Politics: 2.5%Pessimism Bias7.8%This article: 36.1%The Noticer: 9.5%CNN Politics: 14.3%Negativity Bias36.1%This article: 0.0%The Noticer: 1.2%CNN Politics: 0.3%Self-Serving Bias0.0%This article: 6.2%The Noticer: 3.0%CNN Politics: 1.8%Fundamental Attribution Error6.2%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.0%Actor-Observer Bias0.0%This article: 12.5%The Noticer: 6.5%CNN Politics: 3.0%In-Group Bias12.5%This article: 3.1%The Noticer: 14.8%CNN Politics: 5.2%Out-Group Homogeneity Bias3.1%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.5%Halo Effect0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.8%Horn Effect0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 1.8%Recency Bias0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.2%Primacy Effect0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.0%Blind-Spot Bias0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 2.3%Ad Hominem0.0%This article: 4.7%The Noticer: 1.2%CNN Politics: 0.9%Straw Man4.7%This article: 0.0%The Noticer: 0.0%CNN Politics: 1.7%Appeal to Authority0.0%This article: 7.8%The Noticer: 1.9%CNN Politics: 0.9%False Dilemma7.8%This article: 0.0%The Noticer: 1.2%CNN Politics: 2.1%Slippery Slope0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.0%Circular Reasoning0.0%This article: 17.7%The Noticer: 23.9%CNN Politics: 10.9%Hasty Generalization17.7%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.3%Red Herring0.0%This article: 5.8%The Noticer: 6.0%CNN Politics: 0.7%Bandwagon5.8%This article: 8.2%The Noticer: 6.6%CNN Politics: 4.7%Appeal to Emotion8.2%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.9%Begging the Question0.0%This article: 11.3%The Noticer: 2.8%CNN Politics: 2.5%Post Hoc (False Cause)11.3%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.3%Tu Quoque0.0%This article: 10.3%The Noticer: 2.6%CNN Politics: 0.8%Burden of Proof10.3%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.0%Appeal to Nature0.0%This article: 5.8%The Noticer: 1.5%CNN Politics: 0.2%Composition/Division5.8%This article: 40.5%The Noticer: 36.6%CNN Politics: 7.0%Anecdotal40.5%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.1%No True Scotsman0.0%This article: 11.9%The Noticer: 3.0%CNN Politics: 1.3%Ambiguity (Equivocation)11.9%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.0%Gambler’s Fallacy0.0%This article: 6.0%The Noticer: 1.5%CNN Politics: 0.1%Middle Ground6.0%This article: 0.0%The Noticer: 1.1%CNN Politics: 0.1%Personal Incredulity0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.0%Special Pleading0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.6%Genetic Fallacy0.0%This article: 11.9%The Noticer: 3.0%CNN Politics: 4.0%Unattributed Quote11.9%This article: 3.5%The Noticer: 2.2%CNN Politics: 2.4%Quote-first Misdirection3.5%This article: 4.7%The Noticer: 1.6%CNN Politics: 9.1%Biased Writer Voice4.7%This article: 0.0%The Noticer: 0.0%CNN Politics: 2.5%Indoctrination0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.1%Politically Left Leaning Bias0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 5.2%Politically Right Leaning Bias0.0%This article: 0.0%The Noticer: 0.0%CNN Politics: 0.2%Attempt to Sell a Product or S…0.0%

513 words analyzed.

Speakers

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Analysis

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