The other day I was working with a Master Carpenter. What impressed me was how many tools he had in his shop. Some I could identify, others not so much.
As an omniscient law librarian, I have many tools at my disposal, too, and have used many legal databases in my time teaching and research law and legal things.
The problem with using legal databases like Westlaw or Lexis or Bloomberg Law or Fastcase, Anylaw.com, etc. is that you (as in the individual) have to come up with a search string(s) that you hope will dig up whatever it is you're looking for.
What is a search string?
While you can always run searches using natural language (like what most people do in Google), a search string typically uses more complex terminology. It's like it's own programming language and when you get into it, it really helps to narrow down your search results to the point where you can really dial into what it is you actually need.
Formally called Boolean search syntax, a Boolean search syntax uses terms and connectors to help narrow search results.
Boolean search connectors common to most all browsers and legal databases include:
And if all you're going to use is your common, everyday browsers, these will work great.
However, if you're ever going to step up and play with the big dogs, you're going to need to know how to develop a proper Boolean search syntax using one (if not all) of the more powerful legal databases.
My personal favorite legal database is Westlaw. Powerful, tons of features and, best of all, easy to teach and use. A bit on the pricey side if you're looking to get personal access, but it is hands-down the best resource when it comes to searching all things legal.
Back in the day, I was pretty good at developing my own search strings. When I got stumped, I'd waste not a second and call 1-800-Westlaw and speak with a Reference Attorneys (bunch of lawyers who ate, slept and lived Westlaw 24/7) to get help drafting a search query.
However, with the advent of Artificial Intelligence (aka AI), coming up with a search string is easier. So, let's say I searching in Westlaw for caselaw for/to:
Create a search string using terms and connectors seeking cases since 2015 where an amusement or theme park was held liable for injuries to guests
In this case, I used Chatgpt and retrieved the following result:
("amusement park" OR "theme park" OR "water park") /p (guest OR patron OR visitor OR invitee OR customer OR "paying customer") AND (liab! OR "held liable" OR "found liable" OR "liable for" OR "judgment for plaintiff" OR "verdict for plaintiff") /s (injur! OR accident OR mishap OR death OR "wrongful death" OR harm OR "personal injury" OR "bodily injury" OR "catastrophic injury" OR "traumatic injury" OR "fall injury" OR "ride injury" OR "slip and fall") AND (neglig! OR "duty of care" OR "breach of duty" OR "premises liability" OR "premises defect" OR "failure to warn" OR "inadequate security" OR "inadequate maintenance" OR "dangerous condition" OR "attractive nuisance") /p ("amusement park" OR "theme park" OR "water park") DA(aft 01-01-2005)
So, here we have a number of connectors like:
OR (give me A or B; more expansive)
AND(give me A and B (more restrictive)
/p (A within the same paragraph as B - expansive)
/s (A within the same sentence as B - bit more restrictive)
! (acts as an extender. So, Act! retrieves Act, Acts, Acting, Acted, Acted, Actor, Actress...)
( ) (keeps related concepts together)
" " (returns two or more words together in a certain sequence)
DA (refers to a date filter)
With a date filter of 2015-2025, we'll see things we are looking for. Or, at lease we can get to a starting point.
Lexis is another legal database. Not my favorite as it is a pain to teach and it is still has some clumsy elements.
Using the same criteria as above (create a complex search string using terms and connectors seeking
cases since 2015 where an amusement or theme park was held liable for
injuries to guests) and using Chatgpt, our search string looks like:
("amusement park" OR "theme park" OR "water park") w/15 (guest OR patron OR visitor) AND (liability OR "held liable" OR "found liable" OR "judgment for plaintiff") w/15 (injury OR injuries OR accident OR death OR "wrongful death" OR harm OR "personal injury") AND (negligence OR "duty of care" OR "premises liability" OR "attractive nuisance") AND NOT ("judgment for defendant" OR "defense verdict" OR reversed)
Again we have a number of connectors like:
AND (A and B - less restricted)
OR (A or B - more restricted)
AND NOT (A but don't include any results with B - even more restricted)
w/# (I want A within a certain number of words)
( ) (keep this cluster of terms together
" " (I want these words in just this order)
Also to note is that Chatgpt added some legal terms like "premises liability," "attractive nuisance," and "wrongful death" suggesting that it is trying to give additional suggestions as users conduct a search.
Note also that this search query isn't as long or complex as the one for Westlaw. That doesn't mean it's wrong or anything - it's just different and it's how Chatgpt interpreted what I was asking. Change the query, and I'd get another result.
The bottom line here is that AI had really changed how law people work. No longer do we have to hunt and peck around hoping to hit pay dirt. Now we have AI search engines which help to cut down the time that is used to take to get started.
Once upon a time, I lived in the big sky country (i.e.Montana). Beautiful. Majestic. Lots of open road, hunting, fishing, camping - Montana has a little bit of everything when it comes to the great outdoors.
While I was living in Montana, a story came over the news wire about two guys who went out hunting deer. Seems they had collected deer tags from a couple dozen people in the town where they lived and had shot a whole lot of deer.
Turns out they shot more deer than they had tags so they buried the ones that didn't have tags under the ones that did hoping Fish and Game Wardens wouldn't be catch them.
Sensing something was wrong when a trailer full of deer drove by, Fish and Game actually did go through all the deer, found the un-tagged deer aaaaaand confiscated the who kit and caboodle.
So, why am I telling you about this? The other day as I was standing in line to buy a single bottle of soda and I had the priviledge of standing in line behind a, extreme couponer.
You know (or have heard) of the type.
They collect hundreds of coupons and dole them out when they buy stuff so that at the end they only have to pay pennies on hundreds of dollars of stuff.
Well, Couponer is going through all their coupons. Manager is getting upset. I mean, Couponer must have had three hundred coupons and Manager was checking each one careful enough that he started noticing something fishy.
Legitimate extreme couponers can sometimes get bills down to pennies, but only when:
The coupons are valid and stackable under store policy.
There are simultaneous sales and rebates.
The store accepts multiple coupons per transaction.
So, after Couponer has gone through a couple hundred coupons, Manager starts to notice that the dates on some of the coupons were off by a couple months.
I suspect Manager normally ignores such things to maintain good standing in the community but in the case of someone using hundreds of fake or misapplied coupons, that’s fraud - even if the register “takes” them at checkout.
In case you're wondering, coupon fraud is the intentional misuse, alteration, counterfeiting, or unauthorized reproduction of coupons—paper, digital, or mobile—in order to obtain goods or services for free or at a reduced price in a way that violates the coupon’s terms and conditions, store policy, or applicable law.
In other words, it’s using coupons deceptively to secure savings you’re not entitled to.
So, picture it: Couponer has gone through a couple hundred coupons and Manager sees that Couponer has included a couple dozen out of date coupons. Good faith or not, Manager points out the discrepancies, Couponer feigns ignorance, Manager voids the entire transaction and kicks Couponer out of the store aaaaaaand I finally get to buy my soda.
While I don't know if what Couponer did rose to the level of fraud, I guess the moral to the story is, if you think you're going to get away with something, best to have all your ducks in a row and not annoy the manager, the cashier, or the guy behind you who is just trying to buy a soda.
Have you ever gotten emails from people you've never met asking for information that you don't think you should give out?
Maybe a "friend" casually asks you for your user name/password to see what funny stuff you've posted on social media.
Maybe you're searching online at work when, out of the blue you get an email or text from someone you don't know about something like:
Subject: Urgent: Your Amazon account has been compromised!
Dear Customer,
We have detected suspicious activity on your Amazon account. To protect your information, please verify your account by clicking the link below: [Link: Verify your account here: malicious-amazon-login.com]Failure to verify your account within 24 hours will result in account suspension.
You click the link, you computer screen starts to flicker and it shuts off....OR
Nothing happens but a few days later you discover that your username/passwords have been changed making it impossible to access any of the accounts stored in your account manager (you know, where you have been storing your usernames/passwords for the last few years), OR
You get a visit from IT/HR saying that email you clicked from someone you've never met or heard of released a virus into the computer network and it's going to cost the company hundreds of thousands of dollars to fix and, oh yeah, you're fired.
Ever happen to you? If this scenario has happened to you, you, my friend, have become a victim of social engineering.
I remember one time years before the word "social engineering" was even coined, I got a call from an official sounding guy. There were sounds of people talking in the background, typewriters going, secretaries taking dictation, and such.
Sounded legit.
Guy started in asking me questions like can I spell my name, where I lived, how old I was - that sort of thing. Then he asked for my social security number.
Just as I started to say the first number, something caught my attention and I'm like why do you need my SS#? He started saying something and I got the BS feeling in my gut and hung up.
Don't know what the BS feeling is? Essentially, it's if it looks like a duck and flies like a duck but smells like Bulls**t, it's probably not a duck.
Anyway, turns out social engineering happens to LOTS of people and organizations worldwide. In fact, globally, social engineering attacks (including phishing, impersonation, etc.) cost businesses approximately $4.8 billion in 2024—up from about $4.2 billion in 2023.
Wait, what?!
Before we get too deep into this, let's define what Social Engineering is:
Social engineering is a trick used to fool people into giving away private information or doing something they shouldn’t, usually by pretending to be someone they're not in order to gain the trust of their victim(s).
Social engineering manipulates or deceives people into divulging confidential information or performing actions that compromise security (either to the private individual or a corporation). It often relies on psychological manipulation - exploiting human emotions and instincts rather than technical vulnerabilities (like what you might expect from a computer hack).
The success of social engineering lies in the fact that humans are prone to error and therefore fall for manipulative tactics. According to a social engineering attacks survey, “Social engineering attacks are one of the insidious and pervasive threats that compromise the individual’s privacy and security. These malicious strategies exploit an individual’s tendency to trust digital resources...One of the primary causes of social engineering attacks is human error and emotional responses to factors such as greed, fear, empathy, and curiosity.”
Social engineering is often the gateway to technical breaches (e.g., phishing leads to ransomware), but it doesn’t always get the credit—or blame—it deserves. It's less flashy, more human, and harder to track. So, while attacks on computer systems get better press, using social engineering is often more readily employed as it is easier to exploit human weaknesses such as trust, a sense of safety, and the tendency to help others or seek the most convenient path than to go to all the trouble of hacking a computer network.
So, what are some of the more popular ways social engineering happens?
1. Phishing
Fake emails, texts, or messages that look legitimate but trick you into clicking links, downloading malware, or entering personal info.
Example: You get an email that looks like it’s from your bank, asking you to “verify your account.”
2. Vishing (Voice Phishing)
Phone calls where someone pretends to be from tech support, a bank, or government agency to get sensitive info.
Example: “This is Microsoft. We’ve detected a virus on your computer…”
3. Smishing (SMS Phishing)
Phishing via text messages. Usually includes a suspicious link or urgent message.
Example: “Your package is delayed. Click here to reschedule delivery.”
4. Pretexting
The attacker creates a fake identity or situation (a “pretext”) to get you to trust them and share info.
Example: Someone pretends to be HR asking for your Social Security number to “update your file.”
5. Impersonation
The attacker pretends to be someone you know or someone in authority (like a boss or IT support).
Example: A “CEO” emails asking you to urgently wire money for a business deal.
6. Baiting
Luring someone with a tempting offer—like free software, a USB drive, or music downloads—that actually contains malware.
Example: A USB drive labeled “Employee Salaries” left in a company parking lot.
7. Tailgating / Piggybacking
Physically following someone into a restricted area by pretending to be an employee or visitor.
Example: “Oops, I forgot my badge—mind holding the door?”
8. Quid Pro Quo
Offering a service or benefit in exchange for information.
Example: “I’ll fix your printer if you give me your login credentials.”
These methods all rely on exploiting human trust, fear, curiosity, or helpfulness—not just technology. That’s what makes social engineering so powerful and dangerous.
So, how might a social engineering attack play out in real life:
Scenario: "The IT Support Scam"
Target: An employee at a company Attacker’s Goal: Gain login credentials to the company’s internal system
Pretext (The Setup)
The attacker calls the employee pretending to be from the company’s IT department.
"Hi, this is Mike from IT. We’re doing urgent maintenance on the login system, and I noticed your account has been flagged."
Creating Urgency and Trust
The attacker uses technical jargon and time pressure.
"If we don’t fix this now, your access could be locked and flagged for audit. I can help you reset it quickly."
Information Gathering
The attacker asks a few harmless-seeming questions to gather details:
"Can you confirm your username and the last four digits of your employee ID?"
Exploitation
Then comes the real request:
"Now I just need your current password to manually reset the system on our end. After that, I’ll send you a temporary one."
The Hook
The employee, stressed and believing they’re helping IT, provides the password.
Execution
The attacker immediately logs into the employee's account and accesses sensitive company data or plants malware.
What just happened? The attacker didn’t hack any system—they hacked human trust. That’s social engineering in real time: manipulating someone into voluntarily giving up secure information.
Have you ever had this happen to you? I'll bet it has but you didn't know it.
So, what can you do to protect yourself? Turns out there are a number of things you (or your company) can do to prevent (or, at least, delay the inevitable attack), like:
Recognize the warning signs
Unexpected phone calls. If you get a call you weren’t expecting, especially if the caller says they’re from a bank, insurance, or an IT company, chances are it’s a phishing attempt.
Suspicious email sender’s address. If something feels off about an email you got, always check the sender’s email address because it may be a spam email.
Unusual requests from someone that you may know. If your boss or a manager contacts you with urgent requests for money, credentials, documents, and other information when they've never done that before, it could be a phishing attempt. Always verify.
Urgent requests or demands. Phishing attempts have a sense of urgency to them, such as “pay now” or “act quickly,” all designed to make you feel pressured, distracted, and overwhelmed into acting NOW!
Unexpected links or attachments. Do not open attachments or click on links in emails you were not expecting. They could be malicious, and lead to dangerous sites.
Unusual layout and spelling. Incorrect grammar and spelling, strange sentence structure, and inconsistent formatting are strong indicators of a phishing attempt.
Generic greetings/signature. Greetings that don’t include your name, such as “Sir/Maam,” and signatures without contact information (or contact information that does not make sense) are strong indicators of a phishing email.
Offers that seem too good to be true. If an offer seems too good to be true, such as large amounts of money for seemingly useless information, it could be a phishing attempt.
Requests on social media from someone you don’t recognize. Be wary of messages from people or entities you don’t know.
Implement multi-factor authentication
Multi-factor authentication, specifically phishing-resistant MFA, is a security method that requires users to verify their identity using two or more different types of proof, like a password and a code sent to your phone. The requirement of two or three extra steps lowers the risk of a breach even if attackers already have your credentials.
Train employees on awareness
Regular organization-level training is important to ensure the safety of your employees and data. Employees should be informed about and be taught to use defensive measures such as multi-factor authentication, the importance of the use of strong passwords, and the use of firewalls.
Operate under the zero-trust mindset
Essentially, don't trust anyone. Always assume all incoming communications are social engineering attempts, and proceed with caution. Always be looking for clear evidence that the message is legitimate.
Avoid sharing personal information online
Monitor your social media profiles keeping them private and ONLY share access with people you know personally.
Like the old timey radio show The Shadow instilled in baby-boomers everywhere: Who knows what evil lurks in the hearts of men?
Who, indeed!?
Your best bet is to keep your personal information close to your vest and trust no one because everyone is out to get you (insert evil laugh, here).
You know what really bugs me (well, today, anyway)? It's these laws that are enforceable on "we" the people but "them" the politicians are immune.
I mean, the whole point of the Revolution of 1776 was, among other things, to provide representation in government by the people and for the people.
Instead, what we have are laws that stick it to we the people in favor of select corrupt politicians (and in my book, if you're going to use laws to your benefit and then not allow your constituents whom you are supposed to be representing the same courtesy - you are corrupt).
For example:
1. Campaign Finance & Bribery
Citizens:
Bribing or receiving money for official acts is a federal felony (18 U.S.C. § 201).
Private citizens have been convicted and imprisoned for giving or receiving even small bribes.
Politicians:
Many accept massive campaign donations or “Super PAC” support from those seeking favorable policy.
Citizens United v. FEC, 558 U.S. 310 (2010) made it nearly impossible to prosecute large-scale political donations as bribery.
The McDonnell v. United States, 579 U.S. 550 (2016) Supreme Court decision drastically narrowed what counts as an “official act” — making bribery cases against politicians almost impossible to win.
Why immune: lobbying and campaign donations are protected as “speech”; bribery laws are narrowly interpreted to protect politicians but are broadly interpreted when prosecuting everyone else.
3. Tax Evasion and Financial Disclosure
Citizens:
IRS aggressively pursues underreporting, false deductions, and unreported income.
Some have failed to disclose millions in stock trades, rental income, or gifts without criminal consequence (usually resolved with a fine or “amended filing”).
Why immune: disclosure violations are civil; IRS rarely audits sitting members; ethics committees are political, not judicial.
4. Obstruction of Justice / Perjury
Citizens:
Lying to the FBI, Congress, or courts = felony under 18 U.S.C. § 1001.
Many citizens and government employees have been prosecuted for false statements.
Politicians:
Members of Congress or executive officials frequently give misleading or false testimony under oath with no prosecution (e.g., high-profile hearings).
Enforcement is inconsistent and usually requires the DOJ to prosecute itself or its political allies.
Why immune: political pressure; DOJ discretion; speech or debate clause.
5. Insider Trading
Citizens:
Regular investors are routinely prosecuted by the SEC and DOJ for trading on material, nonpublic information (MNPI).
Penalties: prison (up to 20 years), civil fines, disgorgement of profits, and permanent bans from trading.
Politicians:
Members of Congress have received briefings with MNPI (e.g., COVID-19 briefings before market crashes).
Why immune: difficult to prove “nonpublic” and “intent” elements; political pressure; Congress regulates itself.
It's to this last one that I base my claim because it seems that Congress (you know, the group(s) that is supposed to be representing we the people?) purposely makes laws that secretly include loopholes to help politicians evade prosecution.
As this all relates to Congressional insider trading, while politicians in the U.S. are not techically exempt from insider trading laws, because enforcement is extremely weak (and taking into account the many, MANY loopholes that politicians are aware of and take advantage of), prosecution is nearly impossible in practice.
Here’s a breakdown of why this happens.
The law technically applies to politicians. The Securities Exchange Act of 1934 and Rule 10b-5 prohibit anyone (including members of Congress) from trading stocks based on material, nonpublic information (MNPI). However, for decades, it wasn’t clear whether information obtained through official government work counted as MNPI.
Well, it was clear to regular, every day people who could see what was going on but for whatever reason, politicians (who can't see past the end of their elongated noses) could never see any discrepancies.
The STOCK Act (2012) tried to fix this. After public outrage over reports that members of Congress were trading stocks based on information learned through their duties, Congress passed the Stop Trading on Congressional Knowledge (STOCK) Act in 2012.
The Act explicitly affirmed that Members of Congress, their staff, and executive officials are subject to insider trading laws. It required disclosure of trades within 45 days and it prohibited the use of nonpublic information gained through official position for personal gain.
BUT...
Congress quietly weakened the Act in 2013 — removing the online disclosure database and softening transparency requirements (remember the part about the loopholes?). Consequently, enforcement was left to federal prosecutors and the SEC, who almost never (note the NEVER part) pursue these cases.
There have been a few notable cases where the DOJ investigate insider trading by Congressional "leaders," like:
Sen. Richard Burr (R–NC): As Senate Intelligence Chair, Burr received private briefings about the emerging coronavirus threat. Consequently, he sold major holdings days after those briefings and before markets collapsed.
Date of Trades: February 13, 2020 — just before the U.S. stock market crash caused by COVID-19 fears.
Value of Trades: Between $628,000 and $1.72 million in 33 separate transactions.
The DOJ investigated but declined to prosecute.
Sen. Dianne Feinstein (D-CA): In March 2020, Feinstein came under scrutiny for stock sales shortly before the market crashed due to COVID-19. Feinstein was one of them.
Date of Trades: January–February 2020, early in the COVID-19 pandemic.
Value of Trades: Estimated between $1.5 million and $6 million in Allogene Therapeutics stock (a biotech company).
The DOJ investigated but declined to prosecute (though Feinstein offered to pay a small civil fine - usually up to $50,000, (though the exact amount was not reported publicly).
Sen. Kelly Loeffler (R-GA): accused of selling stocks shortly after attending a closed-door Senate Health Committee briefing on COVID-19 (January 24, 2020), during which public officials warned about the virus’s likely impact.
Date of Trades: January 31 – February 14, 2020 (more than two dozen additional transactions took place over these two weeks.
Value of Trades: Estimated total trades: 27 separate transactions, worth between $1.3 million and $3.1 million.
The DOJ investigated but declined to prosecute.
Sen. James Inhofe (R-OK): In late January 2020, following a closed-door Senate briefing (led by Trump administration officials) about the emerging risks of COVID-19, Inhofe sold off significant stock holdings just before the market dropped sharply.
More recently, several member of congress have continued to engaged in insider trading despite the increased scrutiny, such as:
Who: Rep Van Hoyle (D-Oregon)
What: In September 2025, she was "weeks or months" late in disclosing 217 stock trades by her husband, per her congressional financial disclosure.
How Much: The trades' combined value is giving between $45,215 and $3,355,000. Her office later said the specific combined value was about $500,000.
Who: Rep. Sheri Biggs (R-South Carolina)
What: Disclosed multiple trades made by her or her spouse in 2025, including stock sales and purchases.
How Much: The trades improperly disclosed total somewhere between $4.14 million and $13.62 million in value. Some individual transactions: buying and ETF (iShares Bitcoin Trust, "IBIT") in the $100,000-$250,000 range.
Who: Rep. Donald Norcross (D-New Jersey)
What: In September 2025, he filed a financial disclosure more than a year late under the STOCK Act for a stock sale.
How Much: The sale was for up to $50,000 of Toronto-Dominion Bank stock in a retirement account.
Who: Rep. Mike Kelly (R-Pennsylvania)
What: An ethics panel found he violated the House code of Conduct in 2025 in relation to stock purchases by his wife after he allegedly learned confidential information about a plant staying open.
How Much: The profit from that transaction was $64,476.
Of course, there have been several proposed reforms to close the loopholes enjoyed by congressional "leaders."
Requiring
lawmakers to divest from individual stocks within 180 days of the
bill's enactment or within 180 days of taking office.
Applying the ban to future presidential administrations
What is particulary interesting about the Honest Act is that it does have some particularly sharp teeth in the way of penalties if/when Congressional "leaders" violate it, such as:
Daily fines:Fines of $1,000 or more per day that a violation continues.
Forfeiture of profits:Disgorgement of any profits made from prohibited investments.
Increased penalties:Higher fines for failing to make required disclosures under the STOCK Act.
Forfeiture of assets:The potential loss of assets or property involved in a violation.
Criminal penalties:Prison time and larger fines, as specified by criminal statutes
...Buuuuut none of these bills have passed - yet (as of 2025).
So, teeth or no, odds are none of these bills will pass committees or even make it to the desk of the POTUS to be signed.
The bottom line is this: Where countless ordinary citizens are prosecuted whileno politician has ever faced charges for insider trading strongly suggests that the insider trading “rules” for Congress are weak and effectively unenforceable in practice on purpose.
Essentially, what's good for thee is not for me
The failure of government to police itself demonstrates systemic bias, structural loopholes, and political protection, rather than any lack of wrongdoing by the politicians themselves...and it's well past time to change all this.
So, let's hope Sen. Hawley has the cojones(and the Republicans can get out their own way long enough) to get the "Honest" Act passed into law.
Here's a bar bet fact. Did you know that every day, all around the world, Google.com processes 8 BILLION queries? Of those 8 billion search queries using the general search bar at Google.com, only about 0.1% use Advanced Search.
Wait, what???
At about the point, you should be asking yourself, what's Advanced Search?! As noted, there are a few ways to search Google. First is to conduct a general, natural language search using the general search bar at Google.com which is what 7.992 billion users do daily. The other 8 million savvy users use the Advanced Search features. While most all browsers have advance search features, Google has a couple other features up its sleeves to help you get what you're looking for/at.
Before I get into this, I have to warn you, dear reader, that what I'm about to expose you to is pretty deep state sort of stuff. Most people are happy to live their lives in utter ignorance. For the rest of us, just getting along isn't enough. So, ONLY if you're willing to be 1,000,000,000.9% vested, you might want to hit the pause button here, take the blue pill and go back to to your "regular" programming.
For the rest of you...
To help understand the difference between "Regular" searching and "Advanced Search," we have to look at results.
Let's run a search using the "normal" search bar in google and run a search for:
Law cases since 2005 where an amusement park was held liable for injuries to guests
While Google doesn't say how many results were returned anymore, you do get an inkling that you got a lot of stuff that may or may not be directly relevant to what you're looking for/at:
The thing with Google is that anything after the first page is going to be questionable. It might be relevant but probably isn't and it gets more and more frustrating the further away you get from that first page of results.
Now, let's run a search in Advanced Search. To do this, Type Advance Search in the Google Search bar, thus:
Hit Enter and you'll get (or should get):
Click "Advanced Search" and you'll see:
For this search, we're going to be using the rows:
All These Words
This Exact Word or Phrase
Any of These Words
Numbers Ranging From
Using our above search (Law cases since 2005 where an amusement park was held liable for injuries to guests), we can extract a few keywords to help our search.
Under "All These Words," I'm going to enter the words: negligence liable. A simple definition of negligence is you didn't mean to do it. A simple definition of liable is that you are responsible. I want these words because they form the basis of most injury cases. Also, just because you didn't mean to do it (or something), doesn't mean you aren't liable for injuries to another.
Under "This Exact Word or Phrase," I'm going to search for: "amusement park" or "theme park" or "held liable." I put quotes around two or more words because I want to keep those two words together in just that order (i.e. I don't want park amusement because that doesn't make sense). Also, I'm using the word "or" to indicate that I'll take what I can get. Like a hail Mary pass
Under "Any of These Words," I'm going to enter: injuries injury accident harm death. Notice that I don't use commas between the words. I've just gotten in the habit of not using commas and just type the words as I need.
Finally, under "Numbers Ranging From," I'll use my date range of cases from 2005 to 2025.
Hit enter and you'll get something that looks like:
While this is just the AI summary of the results, we can see several of our search terms like "Amusement park," "held liable," injuries, and negligence. As we scroll down, we can find results related to our search query:
As you look at each result, you can see our search terms specific to our search as well as the years (which are within our search parameter of 2005-2025).
The problem with all this is that while nice, these results don't actually get us what we're seeking. Specifically, we were looking for legal CASES related to injuries at amusement parks.
To see cases FOR FREE, we're going to need to search under Scholar.Google.com. To get there, simply search for scholar.google.com in the search bar, hit enter and voila!
What you should notice is options. If you want to search for general scholarly articles, select "Articles." If what you want is case law (as is what we're looking for, here), select "Case Law."
When you select Case Law, you will be give another set of options. Specifically, do you want cases from Federal courts, courts from the jurisdiction from where you are using Google (since I am presently in Utah, "Utah courts" is identified), or would you like to select cases from other jurisdictions (i.e. "Select courts").
While there are amusement or theme parks in Utah, it isn't well known to have such. So, let's expand our search to include Cases from California (theme park of the nation), Florida, Texas, and South Carolina. Then we'll type in our search query with a bunch of "OR" statements:
Hit enter and you'll get something that looks like:
Two things to note. First, scrolling down, you'll find cases from California, Texas, Utah, Florida, and South Carolina and some federal cases (which are the jurisdictions we selected to specifically search). You can also select any year(s) between 2005-2025.
The other thing to note is that you'll see me saying "you'll see something like..." What this means is that every time I hit enter, the results I get are going to be a little different. If you were to run the same search using the same parameters in another month, you'll get different results. It's not that the results are wrong - just updated from when I ran my search.
And there you have it. Dark deep search techniques available to everyone but used only by the few, the proud, the research gods.
Do this long enough and you start getting goose bumps.
