Anyone

cross-posted from: https://slrpnk.net/post/19720959

Political scientists and economists have traditionally argued the more economic prosperity a country has, the more democratic it becomes - but Professor Ian MacKenzie from University of Queensland’s School of Economics in Australia says the relationship is not simple.

“When a country’s income is very low, survival is the focus and the marginal benefits of consumption of material goods is very high,” Professor MacKenzie said.

“Essentially, when you don’t have much, an extra dollar is very, very valuable to you.

“Because of that, you won’t invest time in political activism, you’ll invest it in working to increase your income.”

Professor MacKenzie, along with economists Dr Dario Debowicz (Swansea University), Professor Alex Dickson (University of Strathclyde, Glasgow) and Associate Professor Petros Sekeris (Toulouse Business School), looked at data from every country between 1800 to 2010 to analyse their income and democratic score.

They hypothesised the relationship between the income of a country and its level of democracy is not linear but instead forms a U-shape.

Professor MacKenzie said when societies reach a high level of income, the curve shifts towards increased democratisation.

“As income increases, there comes a turning point at which your income has increased so much you start to value improvements in political freedoms,” he said.

“People feel more empowered to challenge authorities.

“A lot of people believe there is no link between income and democracy, or that there is a positive link – as in more income equals more democracy.

“What we’ve shown is that it’s more complicated than that.”

Professor MacKenzie said China was a country to watch in that it has experienced extraordinary economic growth over the past 4 decades while remaining an authoritarian state.

“The U-shaped theory suggests political uprisings could occur if economic growth continues,” he said.

“China has many citizens who are benefitting from the country opening its markets and increasing its GDP (gross domestic product) so there’s a lot of evidence to suggest they may start craving democratic principles.”

The research was published in Springer Nature.

Political scientists and economists have traditionally argued the more economic prosperity a country has, the more democratic it becomes - but Professor Ian MacKenzie from University of Queensland’s School of Economics in Australia says the relationship is not simple.

“When a country’s income is very low, survival is the focus and the marginal benefits of consumption of material goods is very high,” Professor MacKenzie said.

“Essentially, when you don’t have much, an extra dollar is very, very valuable to you.

“Because of that, you won’t invest time in political activism, you’ll invest it in working to increase your income.”

Professor MacKenzie, along with economists Dr Dario Debowicz (Swansea University), Professor Alex Dickson (University of Strathclyde, Glasgow) and Associate Professor Petros Sekeris (Toulouse Business School), looked at data from every country between 1800 to 2010 to analyse their income and democratic score.

They hypothesised the relationship between the income of a country and its level of democracy is not linear but instead forms a U-shape.

Professor MacKenzie said when societies reach a high level of income, the curve shifts towards increased democratisation.

“As income increases, there comes a turning point at which your income has increased so much you start to value improvements in political freedoms,” he said.

“People feel more empowered to challenge authorities.

“A lot of people believe there is no link between income and democracy, or that there is a positive link – as in more income equals more democracy.

“What we’ve shown is that it’s more complicated than that.”

Professor MacKenzie said China was a country to watch in that it has experienced extraordinary economic growth over the past 4 decades while remaining an authoritarian state.

“The U-shaped theory suggests political uprisings could occur if economic growth continues,” he said.

“China has many citizens who are benefitting from the country opening its markets and increasing its GDP (gross domestic product) so there’s a lot of evidence to suggest they may start craving democratic principles.”

The research was published in Springer Nature.

The benefits of democratic societies go beyond greater personal freedoms and liberties. A new study by a UC Riverside economics professor has found that democratic systems of government also lead to higher participation by women in the labor market.

[...]

To understand this phenomenon, [UC Riverside Associate Professor and study author Ugo Antonio] Troiano found evidence that democratic rule reduces discriminatory attitudes toward women in the workplace.

[...]

The study also suggests that democracies create more female role models, further encouraging women to enter the labor force.

Troiano said his findings align with what we know from political economy and development economics: people are inspired by leaders who resemble them. If all political figures are men, young boys are more likely to aspire to leadership positions, while girls are not. Democracies help correct such imbalances.

“The role model hypothesis suggests that when young women see other women in professional roles during their impressionable years, they are more likely to pursue careers themselves,” he said. “Male dictators may serve as role models only for boys, while female politicians, who are more common in democracies, are more likely to inspire girls as well.”

[...]

Troiano’s findings carry important implications for policymakers. Policies that protect democracy are not just about protecting political rights—they also have tangible economic benefits, particularly for women. Free and fair elections, gender-inclusive governance, and legal protections for women may also be effective tools for increasing female labor market participation and the resulting economic benefits, Troiano said.

[...]

Previous research shows that greater female participation in the workforce can lead to reduced poverty, higher GDP growth, and increased innovation.

Troiano’s research builds on the work of Harvard University economist Claudia Goldin, who won the 2023 Nobel Prize in Economics for research that documented the historical barriers women face in the workforce and the economic factors influencing gender disparities. While Goldin provided a historical and economic analysis of gender disparities, Troiano demonstrated how political and institutional structures around the globe influence these disparities over time.

[...]

cross-posted from: https://slrpnk.net/post/19676598

The copyright status of digital content shared online is often unclear, hindering its reuse. To address this issue, the CommonsDB initiative, funded by the European Commission, is building a prototype registry of Public Domain and openly licensed works. To enhance legal certainty for digital content reuse, the registry will employ decentralized identifiers for consistent content and rights recognition.

[...]

The copyright status of digital content shared online is often unclear, hindering its reuse. To address this issue, the CommonsDB initiative, funded by the European Commission, is building a prototype registry of Public Domain and openly licensed works. To enhance legal certainty for digital content reuse, the registry will employ decentralized identifiers for consistent content and rights recognition.

[...]

cross-posted from: https://slrpnk.net/post/19675447

Archived version

Here is an Invidious link for the video (and 'Lola' part starts at ~5 minutes)

To demonstrate this, Sadoun introduces the audience to “Lola,” a hypothetical young woman who represents the typical web user that Publicis now has data about. “At a base level, we know who she is, what she watches, what she reads, and who she lives with,” Sadoun says. “Through the power of connected identity, we also know who she follows on social media, what she buys online and offline, where she buys, when she buys, and more importantly, why she buys.”

It gets worse. “We know that Lola has two children and that her kids drink lots of premium fruit juice. We can see that the price of the SKU she buys has been steadily rising on her local retailer’s shelf. We can also see that Lola’s income has not been keeping pace with inflation. With CoreAI, we can predict that Lola has a high propensity to trade down to private label,” Sadoun says, meaning that the algorithm apprehends whether Lola is likely to start buying a cheaper brand of juice. If the software decides this is the case, the CoreAI algo can automatically start showing Lola ads for those reduced price juice brands, Sadoun says.

cross-posted from: https://slrpnk.net/post/19675447

Archived version

Here is an Invidious link for the video (and 'Lola' part starts at ~5 minutes)

To demonstrate this, Sadoun introduces the audience to “Lola,” a hypothetical young woman who represents the typical web user that Publicis now has data about. “At a base level, we know who she is, what she watches, what she reads, and who she lives with,” Sadoun says. “Through the power of connected identity, we also know who she follows on social media, what she buys online and offline, where she buys, when she buys, and more importantly, why she buys.”

It gets worse. “We know that Lola has two children and that her kids drink lots of premium fruit juice. We can see that the price of the SKU she buys has been steadily rising on her local retailer’s shelf. We can also see that Lola’s income has not been keeping pace with inflation. With CoreAI, we can predict that Lola has a high propensity to trade down to private label,” Sadoun says, meaning that the algorithm apprehends whether Lola is likely to start buying a cheaper brand of juice. If the software decides this is the case, the CoreAI algo can automatically start showing Lola ads for those reduced price juice brands, Sadoun says.

Archived version

Here is an Invidious link for the video (and 'Lola' part starts at ~5 minutes)

To demonstrate this, Sadoun introduces the audience to “Lola,” a hypothetical young woman who represents the typical web user that Publicis now has data about. “At a base level, we know who she is, what she watches, what she reads, and who she lives with,” Sadoun says. “Through the power of connected identity, we also know who she follows on social media, what she buys online and offline, where she buys, when she buys, and more importantly, why she buys.”

It gets worse. “We know that Lola has two children and that her kids drink lots of premium fruit juice. We can see that the price of the SKU she buys has been steadily rising on her local retailer’s shelf. We can also see that Lola’s income has not been keeping pace with inflation. With CoreAI, we can predict that Lola has a high propensity to trade down to private label,” Sadoun says, meaning that the algorithm apprehends whether Lola is likely to start buying a cheaper brand of juice. If the software decides this is the case, the CoreAI algo can automatically start showing Lola ads for those reduced price juice brands, Sadoun says.

cross-posted from: https://slrpnk.net/post/19631567

Archived

The Tow Center for Digital Journalism at the Columbia University in the U.S. conducted tests on eight generative search tools with live search features to assess their abilities to accurately retrieve and cite news content, as well as how they behave when they cannot.

Results in brief:

• Chatbots were generally bad at declining to answer questions they couldn’t answer accurately, offering incorrect or speculative answers instead.
• Premium chatbots provided more confidently incorrect answers than their free counterparts.
• Multiple chatbots seemed to bypass Robot Exclusion Protocol preferences.
• Generative search tools fabricated links and cited syndicated and copied versions of articles.
• Content licensing deals with news sources provided no guarantee of accurate citation in chatbot responses.

[...]

Overall, the chatbots often failed to retrieve the correct articles. Collectively, they provided incorrect answers to more than 60 percent of queries. Across different platforms, the level of inaccuracy varied, with Perplexity answering 37 percent of the queries incorrectly, while Grok 3 had a much higher error rate, answering 94 percent of the queries incorrectly.

[...]

Five of the eight chatbots tested in this study (ChatGPT, Perplexity and Perplexity Pro, Copilot, and Gemini) have made the names of their crawlers public, giving publishers the option to block them, while the crawlers used by the other three (DeepSeek, Grok 2, and Grok 3) are not publicly known.We expected chatbots to correctly answer queries related to publishers that their crawlers had access to, and to decline to answer queries related to websites that had blocked access to their content. However, in practice, that is not what we observed.

[...]

The generative search tools we tested had a common tendency to cite the wrong article. For instance, DeepSeek misattributed the source of the excerpts provided in our queries 115 out of 200 times. This means that news publishers’ content was most often being credited to the wrong source.

Even when the chatbots appeared to correctly identify the article, they often failed to properly link to the original source. This creates a twofold problem: publishers wanting visibility in search results weren’t getting it, while the content of those wishing to opt out remained visible against their wishes.

[...]

The presence of licensing deals [between chat bots and publishers] didn’t mean publishers were cited more accurately [...] These arrangements typically provide AI companies direct access to publisher content, eliminating the need for website crawling. Such deals might raise the expectation that user queries related to content produced by partner publishers would yield more accurate results. However, this was not what we observed during tests conducted in February 2025

[...]

These issues pose potential harm to both news producers and consumers. Many of the AI companies developing these tools have not publicly expressed interest in working with news publishers. Even those that have often fail to produce accurate citations or to honor preferences indicated through the Robot Exclusion Protocol. As a result, publishers have limited options for controlling whether and how their content is surfaced by chatbots—and those options appear to have limited effectiveness.

[...]

cross-posted from: https://slrpnk.net/post/19631567

Archived

The Tow Center for Digital Journalism at the Columbia University in the U.S. conducted tests on eight generative search tools with live search features to assess their abilities to accurately retrieve and cite news content, as well as how they behave when they cannot.

Results in brief:

• Chatbots were generally bad at declining to answer questions they couldn’t answer accurately, offering incorrect or speculative answers instead.
• Premium chatbots provided more confidently incorrect answers than their free counterparts.
• Multiple chatbots seemed to bypass Robot Exclusion Protocol preferences.
• Generative search tools fabricated links and cited syndicated and copied versions of articles.
• Content licensing deals with news sources provided no guarantee of accurate citation in chatbot responses.

[...]

Overall, the chatbots often failed to retrieve the correct articles. Collectively, they provided incorrect answers to more than 60 percent of queries. Across different platforms, the level of inaccuracy varied, with Perplexity answering 37 percent of the queries incorrectly, while Grok 3 had a much higher error rate, answering 94 percent of the queries incorrectly.

[...]

Five of the eight chatbots tested in this study (ChatGPT, Perplexity and Perplexity Pro, Copilot, and Gemini) have made the names of their crawlers public, giving publishers the option to block them, while the crawlers used by the other three (DeepSeek, Grok 2, and Grok 3) are not publicly known.We expected chatbots to correctly answer queries related to publishers that their crawlers had access to, and to decline to answer queries related to websites that had blocked access to their content. However, in practice, that is not what we observed.

[...]

The generative search tools we tested had a common tendency to cite the wrong article. For instance, DeepSeek misattributed the source of the excerpts provided in our queries 115 out of 200 times. This means that news publishers’ content was most often being credited to the wrong source.

Even when the chatbots appeared to correctly identify the article, they often failed to properly link to the original source. This creates a twofold problem: publishers wanting visibility in search results weren’t getting it, while the content of those wishing to opt out remained visible against their wishes.

[...]

The presence of licensing deals [between chat bots and publishers] didn’t mean publishers were cited more accurately [...] These arrangements typically provide AI companies direct access to publisher content, eliminating the need for website crawling. Such deals might raise the expectation that user queries related to content produced by partner publishers would yield more accurate results. However, this was not what we observed during tests conducted in February 2025

[...]

These issues pose potential harm to both news producers and consumers. Many of the AI companies developing these tools have not publicly expressed interest in working with news publishers. Even those that have often fail to produce accurate citations or to honor preferences indicated through the Robot Exclusion Protocol. As a result, publishers have limited options for controlling whether and how their content is surfaced by chatbots—and those options appear to have limited effectiveness.

[...]

Archived

The Tow Center for Digital Journalism at the Columbia University in the U.S. conducted tests on eight generative search tools with live search features to assess their abilities to accurately retrieve and cite news content, as well as how they behave when they cannot.

Results in brief:

• Chatbots were generally bad at declining to answer questions they couldn’t answer accurately, offering incorrect or speculative answers instead.
• Premium chatbots provided more confidently incorrect answers than their free counterparts.
• Multiple chatbots seemed to bypass Robot Exclusion Protocol preferences.
• Generative search tools fabricated links and cited syndicated and copied versions of articles.
• Content licensing deals with news sources provided no guarantee of accurate citation in chatbot responses.

[...]

Overall, the chatbots often failed to retrieve the correct articles. Collectively, they provided incorrect answers to more than 60 percent of queries. Across different platforms, the level of inaccuracy varied, with Perplexity answering 37 percent of the queries incorrectly, while Grok 3 had a much higher error rate, answering 94 percent of the queries incorrectly.

[...]

Five of the eight chatbots tested in this study (ChatGPT, Perplexity and Perplexity Pro, Copilot, and Gemini) have made the names of their crawlers public, giving publishers the option to block them, while the crawlers used by the other three (DeepSeek, Grok 2, and Grok 3) are not publicly known.We expected chatbots to correctly answer queries related to publishers that their crawlers had access to, and to decline to answer queries related to websites that had blocked access to their content. However, in practice, that is not what we observed.

[...]

The generative search tools we tested had a common tendency to cite the wrong article. For instance, DeepSeek misattributed the source of the excerpts provided in our queries 115 out of 200 times. This means that news publishers’ content was most often being credited to the wrong source.

Even when the chatbots appeared to correctly identify the article, they often failed to properly link to the original source. This creates a twofold problem: publishers wanting visibility in search results weren’t getting it, while the content of those wishing to opt out remained visible against their wishes.

[...]

The presence of licensing deals [between chat bots and publishers] didn’t mean publishers were cited more accurately [...] These arrangements typically provide AI companies direct access to publisher content, eliminating the need for website crawling. Such deals might raise the expectation that user queries related to content produced by partner publishers would yield more accurate results. However, this was not what we observed during tests conducted in February 2025

[...]

These issues pose potential harm to both news producers and consumers. Many of the AI companies developing these tools have not publicly expressed interest in working with news publishers. Even those that have often fail to produce accurate citations or to honor preferences indicated through the Robot Exclusion Protocol. As a result, publishers have limited options for controlling whether and how their content is surfaced by chatbots—and those options appear to have limited effectiveness.

[...]

cross-posted from: https://slrpnk.net/post/19515961

Archived version

Nearly 200 advocacy groups have urged [U.S.] Democratic representatives to “proactively and affirmatively” reject potential industry attempts to obtain immunity from litigation.

“We have reason to believe that the fossil fuel industry and its allies will use the chaos and overreach of the new Trump administration to attempt yet again to…shield themselves from facing consequences for their decades of pollution and deception,” reads a letter to Congress on Wednesday. It was signed by 195 environmental groups such as the Sierra Club, Earthjustice, and Sunrise Movement; legal nonprofits including the American Association for Justice and Public Justice; and dozens of other organizations.

Over the last decade, states and municipalities have brought more than 30 lawsuits accusing big oil of intentionally covering up the climate risks of their products, and seeking potentially billions in damages. The defendants have worked to kill the cases, with limited success.

Now, with Republicans in control of the White House and both congressional chambers, advocates fear the industry will go further, pursuing total immunity from all existing and future climate lawsuits. To do so, they could lobby for a liability waiver like the one granted to the firearms industry in 2005, which has successfully blocked most attempts to hold them accountable for violence.

[...]

[Edit typo.]