Five Great Reads: Addiction, Revenge Quitting, and More

Five Great Reads: Addiction, Revenge Quitting, and More

theguardian.com

Five Great Reads: Addiction, Revenge Quitting, and More

This week's Five Great Reads features articles on addiction, revenge quitting, the making of the Australian television landmark Blue Murder, social media's pregnancy predictions, and the rise of the 'trad family' movement in the US.

English
United Kingdom
TechnologyOtherAddictionAustralian TelevisionRevenge QuittingSocial Media AlgorithmsTraditional Family Values
None
Kirsten SmithRichard RoxburghRoger RogersonKathryn WheelerMike ThomasJenny ThomasChristina Inge
How does social media influence the "revenge quitting" trend, and what are its potential consequences?
Social media amplifies the "revenge quitting" trend by providing a platform for disgruntled employees to publicly express their grievances toward former employers and colleagues. This can lead to increased online visibility for those involved, potentially creating both positive and negative consequences.
What is the central argument of Kirsten Smith, the former addict challenging the brain disease model of addiction?
Smith argues that her addiction-related behaviors stemmed from conscious decisions, contradicting the brain disease model of addiction (BDMA). She contends that BDMA's terminology, such as "chronic" and "disease," can lead individuals with substance-use disorders to view relapse as inevitable.
What are the long-term implications of social media algorithms predicting and serving users with content related to sensitive life events, like pregnancy?
Social media algorithms predicting and serving users with sensitive content, such as pregnancy-related information before the user announces it, raise ethical concerns about privacy and data usage. The algorithms' focus on engagement and revenue generation might prioritize user engagement over user well-being.

Cognitive Concepts

1/5

Framing Bias

The framing of the articles appears neutral, presenting diverse viewpoints without overtly favoring any particular side. Headlines are descriptive rather than sensationalist. However, the inclusion of reading time for each article might subtly prioritize shorter pieces, potentially influencing reader choices.

1/5

Language Bias

The language used is largely neutral and objective. While some articles use descriptive adjectives (e.g., "meaty" for books, "disgruntled" for parishioners), these are generally appropriate to the context and don't exhibit significant bias. The use of "holy smokebomb" is a stylistic choice and doesn't appear to be overtly biased.

2/5

Bias by Omission

The articles, due to their concise nature, necessarily omit substantial details. For example, the article on addiction only briefly touches on the complexities of the BDMA debate. This omission is likely a consequence of space constraints rather than intentional bias, though readers might desire more nuanced discussion.

2/5

False Dichotomy

The article on the 'trad family' movement presents a dichotomy between progressive and traditional viewpoints without fully exploring the spectrum of beliefs and approaches. However, the piece attempts to show nuance, exploring the unexpected transition of the Thomas family, so this is not severe.

Sustainable Development Goals

Good Health and Well-being Positive
Direct Relevance

The article discusses addiction and the brain disease model of addiction, highlighting the importance of addressing substance use disorders and promoting mental health. This directly relates to SDG 3, which aims to ensure healthy lives and promote well-being for all at all ages. The discussion around addiction treatment and relapse prevention contributes to the broader goal of improving mental health and reducing substance abuse.