Jumping Into The Deep: Imposter Syndrome, Defining Success and the New Librarian
Bibliographic record
Abstract
This article is adapted from a presentation given at the Ontario Library Association Super Conference, held in Toronto, Ontario, February 1-4, 2017. This presentation brought together 80+ participants, ranging from students to early- and mid-career professionals. The goals of this presentation were to recognize and build a shared understanding of how library and information professionals experience imposter syndrome. Through personal experience and research, ideas of imposter syndrome are explored through the lens of new librarians. This discussion included competition in the job market, burnout rates, and social media. Through experience and research, we aimed to share tips and tools for managing and examining imposter syndrome. Cet article est une adaptation d’une présentation donnée à la Super Conference de l’Ontario Library Association à Toronto, Ontario du 1er au 4 février 2017. Cette présentation a été offerte à un groupe de plus de 80 participants composés d’étudiants ainsi que des professionnels en début et à la mi-carrière. Elle avait comme but de reconnaître et de favoriser une compréhension commune au sein des bibliothécaires et professionnels de l’information vivant le syndrome de l’imposteur. Par le biais d’expériences professionnelles et de la recherche, les idées sur le syndrome de l’imposteur sont examinées du point de vue des nouveaux bibliothécaires. Cette discussion portait sur la compétition sur le marché du travail, les taux d’épuisement professionnel et les médiaux sociaux. Grâce aux expériences et à la recherche, nous voulions partager des stratégies et des outils pour gérer et examiner le syndrome de l’imposteur.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.018 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".