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Record W56999186

What's in a Name? in a Business Where Plain Vanilla Often Rules, Plenty of Institutions Choose Monikers with Special Significance. Some Owe Their Origins to History, Some to Serendipity. We Take a Look at the World of What Banks Call Themselves

2004· article· en· W56999186 on OpenAlexaboutno aff
Steve Cocheo

Bibliographic record

VenueABA banking journal · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBanking Systems and Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsSerendipityLawHistoryPolitical science
DOInot available

Abstract

fetched live from OpenAlex

of Drexel's lawyer was on the phone and he was plainly worried. It was 1988 and the family-owned bank had taken some big steps. After being headquartered for many years in its namesake town in Missouri, the bank had been expanding. That growth led to the decision to not only move the headquarters to another town, but also to build a new building, and, to top it all off, adopt a new name not linked to geography. The new name of Drexel was about to launch? Bank 1. Up until now, things had been going smoothly. Applications had been filed for the change, the new building's opening was only weeks away, signage had been ordered and was en route. And then came a call from a certain Ohio-based bank holding company. It seems that the Ohioans felt that they had dibs on a particular name and all variations of it--everywhere. Hence the panic call from Drexel's lawyer. Joe Balentine, CEO of the then $22 million-assets remembers his first reaction to the lawyer's call: Let's tell them to jump in the lake. But Balentine's attorney warned him that Banc One was a BIG bank with deep pockets. As much as Balentine felt of Drexel had legal rights to its preferred new name, it was plain the bigger player was willing to take the matter to court. A quick-thinking Balentine came up with a novel solution: He said, Okay, let's add a zero to the name and send the application back to the state for approval. And thus did the former of Drexel become known as Bank 10. What's in a name, a bank name? It depends. Sometimes there's a fascinating story or an aggressive marketing idea behind them. Sometimes the name is rooted in history. Sometimes it's an accident of location. And sometimes the connection is more mundane. (And at times an interesting one gets lost. Today's Bank, Vancouver, Wash., is yesterday's news, having been taken over in mid-2003 by another bank.) Often, a bank's name, like 10's, is based on numbers. There are, for instance, 676 First Nationals, four 1st Nationals, and 91 First Federals nationwide, according to FDIC's web database. There are 247 First States and two 1st States. But not everyone could be first, so there are eight Nationals or Federals or Second otherwise. There are a handful of Thirds, only one of them a commercial Sedalia, Mo.'s Third National. That Third, going back to the 1800s, is now part of Central Bancompany of Jefferson City, Mo., and, while it has locally based competition, Third is first among them, by asset size. There are no banks we could find, but there is Fourth Federal Savings in New York City. But we're still counting down. There is New Orleans' Fifth District Savings and Loan. And, finally, there is the famous fractional bank, Fifth Third Bank, of Cincinnati, the result of a long-ago merger of a Fifth and a Third. Some banks have gone beyond this, of course. Some took their names from money itself. In spite of mergers, there are still three Dimes,--two thrifts and one commercial bank--but no pennies. And though there are 20-odd institutions with the word Lincoln somewhere in their name, many don't play up any connection to the president portrayed on the copper cent or the $5 bill. Also in the spare change department, there are five thrifts with Five Cents in their names, all of them Massachusetts institutions. And in Pittsburgh, Pa., and Newark, N.J., you can still deposit your dollars in savings institutions with Dollar in their names. (The more adventurous might try Texas' Guaranty Bond Bank, or either Oklahoma's or Kansas' Stock Exchange banks, although none of these are actually connected with the securities markets.) Some institutions take the completely opposite tack, boiling their name down to the barest essential. For instance, in Indiana, there is an industrial bank called, simply, Thrift Incorporated. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.087
Threshold uncertainty score0.290

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0170.008
Scholarly communication0.0160.022
Open science0.0010.006
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0870.051

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.228
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2004
Admission routes1
Has abstractyes

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