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Court Determines Researchers Not Responsible for Defamation Following Revelation of Altered Data

### Harvard Business School Lawsuit: A Matter of Data, Defamation, and Academic Ethics

Earlier this year, the academic sphere was marked by an extraordinary and widely publicized incident involving Harvard Business School (HBS) and one of its prominent faculty members, Francesca Gino. This case focuses on allegations regarding research misconduct and has raised critical questions about academic ethics, data manipulation, and the legal limits of defamation within the realm of scientific research.

The issue surfaced when an internal inquiry by Harvard Business School determined that Gino, a distinguished behavioral scientist, had committed research misconduct. Typically, such investigations remain confidential; however, this particular case became public following a lawsuit filed by Gino herself, claiming defamation and breach of contract. Since then, the lawsuit has ignited a larger discussion regarding the necessity for transparency in academic research, the obligations of institutions, and the legal safeguards for individuals who bring forth potential misconduct.

#### The Genesis of the Controversy

The situation originated when three scholars—Uri Simonsohn, Leif Nelson, and Joe Simmons—who operate a blog named *Data Colada*, detected unusual data patterns in a number of Gino’s published works. *Data Colada* is recognized for examining behavioral science research closely, frequently spotlighting cases where data seems manipulated or fabricated. Through a series of blog entries, the team highlighted four papers co-authored by Gino, asserting that the data in these research pieces had been altered.

The *Data Colada* group presented their findings to Harvard, prompting the institution to initiate its own investigation. After interviewing the involved researchers and analyzing the original data files, Harvard concluded that research misconduct had transpired. Consequently, Gino was placed on administrative leave, and the university contemplated revoking her tenure. Harvard also informed the journals that had published the papers, stating the data was unreliable and requesting retractions.

#### Gino’s Legal Action

In reaction to these developments, Gino initiated a lawsuit targeting both Harvard and the *Data Colada* researchers. She contended that Harvard had violated its contract with her, defamed her character, and disrupted her professional connections, particularly with her book publisher. She additionally accused the *Data Colada* team of defamation, asserting that their blog entries had harmed her reputation.

Both Harvard and the *Data Colada* researchers sought to dismiss the lawsuit, leading to a significant legal decision that illuminates the interplay of academic freedom, defamation laws, and scientific integrity.

#### The Court’s Decision: A Mixed Verdict for Harvard

The court’s ruling on the motions to dismiss resulted in a mixed verdict for Harvard. A pivotal issue was that Harvard Business School had introduced a provisional policy for addressing research misconduct when allegations against Gino emerged. This raised doubts about whether the university had breached its contract with her, permitting that segment of the lawsuit to move forward.

Nonetheless, the court dismissed the majority of the remaining allegations against Harvard. The judge ruled that notifying Gino’s colleagues about her administrative leave did not equate to defamation. Likewise, the alerts sent to academic journals requesting retractions were not viewed as defamatory. The judge determined that these notifications represented Harvard’s evolving interpretation of its inquiry into the inaccuracies in the data, rather than defamatory remarks.

#### *Data Colada* Researchers Exonerated from Defamation Claims

The *Data Colada* researchers, however, received a favorable outcome in court. All defamation allegations against them were dismissed. The court found that their blog posts, which outlined the questionable data, were based on evidence-supported conclusions and were articulated with the usual caution of scientific writing. This scientific rigor, coupled with the fact that Gino was a public figure due to her high-profile academic status, meant that the accusations did not fulfill the legal criteria for defamation.

The court also emphasized that scientific disputes should be resolved through scientific means, not through litigation. The judge remarked that the *Data Colada* team had provided links to the data sources utilized, enabling readers to assess the evidence and formulate their own conclusions. This level of transparency further shielded the researchers from defamation claims, as it allowed others to verify their findings independently.

#### Consequences for the Scientific Community

The resolution of this case carries broader ramifications for the scientific community. In recent years, online networks of scientists dedicated to identifying and addressing data manipulation and research misconduct have emerged. These initiatives have resulted in retractions, corrections, and, in certain cases, career repercussions for individuals involved in unethical research behaviors.

Nonetheless, these activities come with inherent risks. Researchers and journalists who reveal misconduct often encounter threats of legal action, as demonstrated by this case. The court’s ruling favoring the *Data Colada* researchers conveys a crucial message: provided that allegations are grounded in evidence and articulated with scientific prudence, they are unlikely to be deemed defamatory. This legal shield is vital for preserving the integrity of the scientific record and fostering transparency in research.

#### Conclusion: A

Presenting the 2024 Ig Nobel Prize Recipients: Honoring Unusual and Mind-Expanding Studies

# The Ig Nobel Prizes: Honoring the Whimsical Aspects of Science

The Ig Nobel Prizes, initiated in 1991, constitute an annual occasion that celebrates scientific accomplishments that “first amuse people, and subsequently provoke thought.” Although the research acknowledged by these prizes may appear peculiar or outright strange at a cursory glance, a number of these studies possess significant scientific value and often unearth profound understandings of our surroundings. These awards are a humorous take on the esteemed Nobel Prizes, yet they remind us that inquiry and innovation lie at the core of scientific exploration.

The 2024 Ig Nobel ceremony, conducted online, showcased the standard blend of quirky humor and earnest science, which included 24/7 lectures (where specialists elucidate their research in 24 seconds and subsequently in merely seven words) and a “non-opera” centered around the theme of water. The 2024 Ig Nobel Prize winners exemplify the notion that even the most unconventional studies can provide meaningful insights.

Here’s a glimpse of some of the remarkable winners from this year’s event:

## 1. **Peace Prize: Pigeons as Missile Steering Mechanisms**
**Citation:** B.F. Skinner, for investigations into the practicality of utilizing live pigeons to navigate missile flight trajectories.

During WWII, American psychologist B.F. Skinner suggested an unconventional answer to the challenge of missile steering: pigeons. His initiative, termed “Project Pigeon,” entailed training pigeons to peck at a targeted image projected onto a screen inside a missile. The pigeons were arranged so that their pecking would direct the missile towards its target. Although ultimately categorized as too “fantastical” by military authorities, Skinner’s research showcased the extraordinary cognitive abilities of pigeons and laid the groundwork for subsequent studies in animal behavior.

## 2. **Botany Prize: Flora Imitating Artificial Flora**
**Citation:** Jacob White and Felipe Yamashita, for uncovering that certain real plants can mimic the shapes of nearby artificial plastic foliage.

In a captivating study, White and Yamashita revealed that the vine *Boquila trifoliolata* could imitate not just the leaves of genuine plants but also those of artificial plastic counterparts. This finding raises fascinating inquiries about how plants interact with their surroundings and if they possess a certain type of “vision” that enables them to recognize and imitate the forms of adjacent objects. The research contributes to a burgeoning field suggesting that plants are much more aware and adaptable than once believed.

## 3. **Anatomy Prize: Hair Patterns and Geography**
**Citation:** Marjolaine Willems and team, for examining whether the orientation of hair whorls on human heads is related to geographic regions.

Willems and her colleagues studied if the orientation of hair whorls (clockwise or counter-clockwise) is affected by geographic location. Their research indicated that individuals in the Southern Hemisphere were more likely to have counter-clockwise hair whorls, while those in the Northern Hemisphere tended to have clockwise ones. Although the researchers could not definitively connect this occurrence to environmental elements such as the Coriolis effect, their study adds a fresh perspective to the ongoing discourse regarding nature versus nurture in the formation of physical traits.

## 4. **Medicine Prize: The Efficacy of Painful Placebos**
**Citation:** Lieven A. Schenk and colleagues, for revealing that deceptive medicine with unpleasant side effects may outperform deceptive medicine without side effects.

Schenk and his team examined the “nocebo effect,” where the anticipation of adverse effects can surprisingly amplify the effectiveness of a placebo. In their investigation, participants who received a placebo nasal spray that caused a slight burning sensation reported greater pain alleviation than those who were given a placebo without side effects. This inquiry implies that the perception of side effects can enhance the perceived efficacy of a treatment, even if the treatment itself is inactive.

## 5. **Physics Prize: The Swimming Capability of a Deceased Trout**
**Citation:** James C. Liao, for demonstrating that a deceased trout can ascend upstream within a vortex wake.

Liao’s exploration of fish swimming physics took an unconventional twist when he set out to investigate if a deceased trout could “swim” upstream by leveraging the energy created by swirling vortices in the water. Remarkably, the lifeless fish was able to move upstream without consuming any of its own energy, courtesy of the forces produced by the vortices. This study illuminates how living fish might save energy while swimming and holds potential for designing energy-efficient aquatic machines.

## 6. **Physiology Prize: Mammals Respirating Through Their Anus**
**Citation:** Ryo Okabe and colleagues, for finding that many mammals can indeed breathe through their anus.

Motivated by the loach, a fish that can respire via its intestines, Okabe and his team investigated whether mammals could also utilize their intest…

“1990s Music Industry Hard Drives on the Brink of Breakdown Because of Obsolete HDD Technology”

### The Delicacy of Hard Drives: An Urgent Reminder for Data Preservation

In our digital era, hard drives represent the foundation of data storage, commonly utilized in various sectors for everything from personal documents to vital corporate data. Nevertheless, recent insights from Iron Mountain, a firm specializing in enterprise storage and destruction, indicate that hard drives might not be as dependable for long-term archiving as many assume. Alarmingly, a considerable number of hard drives from the 1990s are now beyond retrieval, raising concerns about the longevity of this storage medium.

#### The Music Industry’s Archival Crisis

Among the sectors most impacted is the music industry, which has depended significantly on hard drives to save digital audio files, mixing sessions, and other essential data. As highlighted by *Mix*, a trade publication devoted to the music field, Iron Mountain has been assigned with the task of archiving media vaults for various entertainment entities. The results are disheartening: around 20% of the hard drives from the 1990s sent to Iron Mountain are completely inaccessible.

Robert Koszela, global director for studio growth and strategic initiatives at Iron Mountain, stressed the seriousness of the matter. “In our industry, when we find a fundamental issue with a format, it’s crucial to inform everyone,” Koszela stated to *Mix*. “It might sound like a promotional pitch, but it’s not; it’s a call to action.”

#### The Ascendancy and Decline of Hard Drives in Archiving

Hard drives became favored over older storage mediums such as spooled magnetic tape, which was susceptible to decay, substrate separation, and disasters like fires. The advent of digital audio workstations and editing software further propelled the transition to hard drives, perceived as more accessible and dependable. However, hard drives carry their unique challenges, particularly for prolonged storage.

In contrast to magnetic tapes, which can occasionally be salvaged post-partial degradation, hard drives are heavily reliant on both their magnetic platters and the reading hardware. Should either part fail, the complete drive may become unreadable. This poses a significant challenge for archival purposes, where data might not be accessed for years or even decades.

#### The “If It Spins” Conundrum

Iron Mountain pointed out that if the magnetic platters within a hard drive can still rotate and are not physically impaired, there might be a possibility to recover the data. However, this scenario is becoming less frequent. Musicians and studios aiming to remaster old tracks are finding that even when hard drives have been maintained in ideal conditions—standard temperature and humidity controls—many have failed beyond restoration.

Koszela recounted a particularly tragic instance: “It’s heartbreaking to witness a project arrive at the studio, a hard drive in a pristine case with the packaging and tags from where it was purchased still intact. Beside it sits a case holding the backup drive. Everything’s organized. And both of them are useless.”

#### Entropy Always Prevails

The dilemma of hard drive failure is not exclusive to the music industry. The larger tech community has long recognized the intrinsic delicacy of digital storage media. A discussion on *Hacker News* following the revelations from Iron Mountain underscored the widespread nature of this issue. As one user succinctly noted, “You can’t rely on any medium, so you duplicate important items repeatedly into new storage. Optical media deteriorates, magnetic media loses charge, bearings jam, flash storage depletes, etc. Entropy always wins, often much quicker than you expect.”

Indeed, no storage solution is exempt from the effects of time. Optical discs such as CD-Rs and DVD-Rs are susceptible to “disc rot,” while flash storage devices, like SSDs, may experience charge loss over time, making data unreachable. Even Linear Tape-Open (LTO), a format intended specifically for long-term tape storage, encounters compatibility challenges across different generations.

#### The Uncertainty of Hard Drive Failure

The understanding that hard drives will inevitably fail is not a new revelation. In 2005, *Ars Technica* published an article regarding the “five stages of hard drive demise,” cautioning users about the certainty of failure. More recently, backup service provider Backblaze presented data indicating that hard drives are most likely to fail within the first three years of their operation, although no drive is entirely safe from malfunction. A 2007 study by Google regarding server drives also exposed that hard drive failures are largely unpredictable, and factors such as temperature are not as crucial as previously assumed.

#### Lessons for the Future

Iron Mountain’s alert serves as a stark reminder that no storage medium is flawless for long-term preservation. Whether you’re a musician, a filmmaker, or a business proprietor, the essential lesson is that data preservation necessitates ongoing vigilance. Relying on a single medium, particularly one as susceptible to failure as hard drives, is a recipe for disaster.

To lessen the threat of data loss, experts advocate for a multi-pr

OpenAI Unveils New “Reasoning” AI Models: o1-preview and o1-mini

# OpenAI Launches “Strawberry” AI Model: A New Dawn for Reasoning and Problem-Solving?

On Thursday, OpenAI unveiled its eagerly awaited “Strawberry” AI language model, officially designated as **OpenAI o1**. This fresh model family, which features variants such as **o1-preview** and **o1-mini**, promises considerable enhancements in reasoning and problem-solving abilities relative to its forerunners. The models are now accessible to **ChatGPT Plus** subscribers and select API users, heralding a new phase in the development of large language models (LLMs).

## What’s Different in OpenAI o1?

OpenAI asserts that **o1-preview** outshines its predecessor, **GPT-4o**, in various essential domains, including competitive programming, mathematics, and scientific reasoning. According to OpenAI, this model has shown remarkable results on benchmarks, like scoring in the **89th percentile** on competitive programming challenges from [Codeforces](https://codeforces.com/contests/) and achieving a remarkable **83%** on a qualifying exam for the **International Mathematics Olympiad**—a notable improvement from GPT-4o’s 13% score.

Nonetheless, despite these enhancements, initial users have observed that o1-preview does not consistently exceed GPT-4o across all metrics. Some have also pointed out the model’s slower response times, which are linked to its multi-step processing method. This lag stems from o1’s new reasoning abilities, which engage in a more complex, step-by-step problem-solving strategy.

### A Fresh Perspective on Reasoning

The standout innovation in OpenAI o1 is its improved reasoning capabilities. OpenAI credits these enhancements to a groundbreaking **reinforcement learning (RL)** training strategy. This method encourages the model to “analyze” problems more thoroughly prior to providing a response, similar to the **chain-of-thought prompting** technique that has been proven to enhance outputs in other LLMs. The model is engineered to iteratively explore various techniques and acknowledge its own errors, culminating in more precise and reflective answers.

This innovative training method proves particularly effective for tasks that necessitate planning and multi-step reasoning, such as intricate programming challenges or scientific inquiries. However, it’s essential to understand that these advancements do not render o1 a “miracle model” that eclipses earlier versions in every manner, as OpenAI product manager **Joanne Jang** warned in a [tweet](https://x.com/joannejang/status/1834286774140498368).

## Benchmark Performance: Remarkable Yet Not Without Challenges

OpenAI has presented several benchmark results to showcase o1’s strengths. Apart from its robust performance in competitive programming and mathematics, the company claims that o1 operates on par with **PhD students** in specific tasks in physics, chemistry, and biology. However, these assertions are expected to face scrutiny as independent researchers and users undertake their own assessments in due course.

It is pertinent to highlight that AI benchmarks are often criticized for their lack of reliability and susceptibility to manipulation. Earlier this year, **MIT Research** [questioned](https://www.fastcompany.com/91073277/did-openais-gpt-4-really-pass-the-bar-exam) some benchmark claims related to GPT-4, indicating that OpenAI’s performance metrics should be approached with skepticism until further validation.

## o1-Mini: A Budget-Friendly Option

In addition to o1-preview, OpenAI has also rolled out **o1-mini**, a more compact and economically viable version of the model. Priced at **80% less** than o1-preview, o1-mini is specifically optimized for coding tasks, presenting a cost-effective solution for developers and companies in need of AI-driven programming support.

## A Varied Array of Abilities

While OpenAI has shared multiple demonstration videos showcasing o1’s prowess in tackling intricate programming tasks and logic puzzles, one particular demonstration has drawn attention for its simplicity: counting the number of “R”s in the word “strawberry.” This task, which has become somewhat of a meme within the AI community, is notoriously challenging for LLMs due to their tokenization of words into data segments. However, o1 successfully completed the task, illustrating its capability to “consider” its own processes and arrive at the correct answer.

This seemingly minor demonstration brings to light one of o1’s most captivating abilities: its capacity to engage with tasks demanding a deeper comprehension of language structure, an area where earlier models have often faltered.

### Initial Hands-On Feedback

Early users of o1-preview have shared their impressions online, with many expressing a measured optimism regarding the model’s potential. **Wharton Professor Ethan Mollick**, for instance,