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Bridge Over Troubled Water

2006· article· en· W2083167067 on OpenAlexaff
Nir Lipsman

Bibliographic record

VenueAcademic Medicine · 2006
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsQueen's University
Fundersnot available
KeywordsSurpriseBattleApprenticeshipBossCraftClichéLeaguePsychologyMedical educationMedicineVisual artsHistorySocial psychologyArtEngineering

Abstract

fetched live from OpenAlex

“Nir, will you be joining us in clinic?” my supervisor asked before his Tuesday morning ritual. Being my first day, I was taken by surprise, and embarrassed, I managed to nod and thought, “As long as by join you mean stand back and out of the way.” Up until this point, I was used to being ignored. I didn't realize that my attitude would quickly change. I had the good fortune during the summer after my second year of medical school to join the research team of a busy surgical specialist in a bustling metropolitan hospital. Not knowing what to expect, I was anticipating a summer of busy work and a constant battle with residents for face time with the professor. The professor, or “The Boss” as he is known, has a reputation for being blunt and to the point, a no-nonsense clinician, who also happens to be a brilliant surgeon. I imagined that any wisdom I could glean, any experience I could absorb over the course of those months, would be invaluable. Joining him in clinic, for example, was quite an experience. With a gaggle of residents and students in tow, the experienced surgeon would navigate seamlessly through a history and physical that would disorient even the keenest medical student. Watching him work, I couldn't help thinking of myself as an apprentice, as a student learning from a master of his craft. The Boss, however, wasn't satisfied with just letting me watch and insisted that I take an active role in his clinic. He assigned me patients to see and report on; it was terrifying yet thrilling, and I appreciated the opportunity. That summer was the first time that an individual physician treated me as an active and equal member of his team. Having become accustomed to the label of “useless medical student,” it was exciting and refreshing to be involved and, even more so, to be valued. Over that summer, research fellows asked for my opinion regarding anatomic localization and The Boss asked that I present an article at the weekly journal club. I had found an environment full of people who not only shared my budding interests, but who were willing to take the time and effort to help me develop them further. That summer, I discovered the confidence I needed to decide that I wanted to be a surgeon. With my preconceptions altered and stereotypes corrected, I finished my summer experience satisfied that my career decision can now be a source of solace rather than a source of continued stress. I lamented for my fellow students who were left to navigate the troubled waters of early career decision making without the benefit of a mentor, or a group of them, as I had over that summer. I realized that such relationships are keys not only for future academic collaborations but are the foundations of personal networks that allow students and practicing professionals to be satisfied with and passionate about their careers. It would be presumptuous to speak on behalf of all medical students; however, it is not a stretch to say that we all want careers that will make us happy, that will challenge us, and that will provide the opportunity to change our patients' lives for the better. Choosing the right career is the most important decision that a medical student will make, and it took a career-affirming summer to help me realize that meaningful mentorship ensures that the decision is not made alone. Nir Lipsman

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.861

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.243
Teacher spread0.233 · 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 teacher head, not a consensus.

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

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

Citations2
Published2006
Admission routes1
Has abstractyes

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