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Judicial behavioral profile

Justice Robert I.
Caloras

New York Supreme Court, Queens County

What Justice Caloras has required, taken from his transcripts, dockets, and decisions (published and unpublished).

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Behavioral summary

In the cited rulings, Justice Caloras checked whether the document or the party’s account actually supported the point being argued. He limited additional discovery by the question it would answer and the need to protect client confidentiality.

These are patterns across the cited decisions, not findings about a disposition toward either side or about any litigant’s character.

Observed patterns

Each pattern is labelled by how many distinct cases show it and footnoted to the ruling. Where the record limits a pattern, the limit stays with it.

Documents had to address the actual dispute

Recurring across three matters

Justice Caloras checked what each document actually proved. A dog registry did not conclusively show who had the better right to possess the dog. The accessibility audit covered a different website. The air-cannon study examined a different distance. Presenting a document did not solve those mismatches.

Preparation point

Show that the document supports the specific point you need to prove.

How it played outSituation, action, outcome
The situation
A party offered a document as decisive proof.
What he did
He checked its subject and the conditions it covered.
What made a difference
The document’s form did not fix the mismatch.
In his words2 quotes

“the compliance audit that was submitted to the court is for a website called "genopalate.com," not the defendant’s website.”

Batista v PhotonLight.com, Inc., at *6. On the audit of a different website.

“Participation in approximately 20 t-shirt tosses does not a qualified witness make”

Swanson v Queens Ball Park Co., LLC, at *5. On estimating the launch angle from about 47 feet away.

In the cited cases3 rulings

Shallo: registry, license, and payment records did not conclusively establish who had the better right to possess the dog.

Batista: an audit of a different website did not show that the defendant’s site had been fixed.

Swanson: a study of impacts from less than a meter away did not address the stadium launch.

He required explanations for changed or conflicting accounts

Recurring across two matters

Justice Caloras checked for problems within the requesting party’s own account.

Preparation point
How it played outSituation, action, outcomeIn his wordsHis quotesIn the cited cases2 rulings

More discovery needed a clear purpose and had to respect client confidentiality

Recurring across two matters

Justice Caloras asked what the additional information would establish.

Preparation point
How it played outSituation, action, outcomeIn his wordsHis quotesIn the cited cases2 rulings

Cited rulings

Every observation traces to one of these decisions. The three behind the free patterns are listed here; the other four are in the full profile.

MatterIndex No.DecidedCitationPattern
Batista v PhotonLight.com, Inc.716741/2023Oct. 15, 20242024 NY Slip Op 51405(U)Pattern 01
Swanson v Queens Ball Park Co., LLC716592/2019May 14, 20242024 NY Slip Op 50587(U)Pattern 01
Shallo v Zarrour712985/20Feb. 25, 20212021 NY Slip Op 50146(U)Pattern 01

Built from the cited written decisions, published as NY Slip Op rulings and cited by printed page. Quotations are as printed, with only quotation-mark typography normalized. Confirm any passage against the decision before relying on it in a filing. OurFirm.ai is not affiliated with or endorsed by the court or any judge.

How to read this profile

Judge AI reports what a judge said and did in cited decisions, and labels how far each observation reaches. It does not forecast outcomes, compute grant rates, or characterize temperament, motive, or bias, and a question from the bench is never reported as a ruling. It informs your judgment; it does not replace it.

How Judge AI is built
Observed conduct
A specific ruling, order, or statement in a cited decision.
Recurring across matters
The same narrow conduct in two or more distinct cited cases. Not a rate.
Repeated within one matter
Several instances inside one litigation. Never counted as corroboration.
Isolated
One cited ruling. Reported, never generalized into a trait.

Other profiled judges

Built the same way, from each judge's own written decisions. Name any judge on your docket and we will build theirs. All New York profiles

Questions about this profile

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How has Justice Caloras treated documents offered as decisive proof?

In the cited rulings he checked the document’s subject and the conditions it covered. An audit of a different website, a study of a different distance, and registry records that did not settle ownership did not decide the point. Those rulings let the cases continue; they did not decide the plaintiffs’ ultimate rights.

Can Judge AI predict how Justice Caloras will rule?

No. Judge AI builds behavioral profiles from real opinions, oral argument transcripts, and docket records so you can see how a judge has responded to arguments like yours before. It informs your judgment; it does not replace it or forecast an outcome.

Where does this profile come from?

From Justice Caloras’s written decisions. The profile cites 7 rulings across 7 cases from 2020 to 2025, each by case name, NY Slip Op citation, and page.

What is in the full profile?

All three observed patterns with every pinpoint, the limits and exceptions the record contains, and the preparation points that follow from them. We walk you through it on a 30-minute call and can build the profile for the judge on your next matter.

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