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203 results for “mentoring”
Figures 7–12. Rolando Teruel Ochoa. Figures 7–8. With his colleague and mentor Luis F in Rolando Teruel Ochoa
Figures 7–12. Rolando Teruel Ochoa. Figures 7–8. With his colleague and mentor Luis F. de Armas (2010 and 2012). Figure 9. With his colleagues and friends Antonín Kůrka and František Kovařík (2010). Figure 10. With his colleague and friend František Kovařík (2010). Figure 11. Looking for scorpions (2010). Figure 12. With his colleagues and friends Tomás M. Rodríguez-Cabrera and František Kovařík (2010).
Supporting material for "Impact of gender on the formation and outcome of formal mentoring relationships in the life sciences"
<p>This repository contains data and analysis code associated with the manuscript: L.P. Schwartz, J. Liénard, S. V. David. (2022) "Impact of gender on formation and outcome of formal mentoring relationships in the life sciences." Figures and tables in the manuscript can be produced by running the make_figures.ipynb notebook. Figures have been marked with headings indicating their position in the manuscript (Figure 1, Figure S1, etc.). In addition, the notebook contains code to reproduce regression analyses that are cited in the text but not directly associated with a figure.</p> <p>Data on mentoring relationships derives from Academic Family Tree (AFT, www.academictree.org) and public data sources on funding, publications, and awards. Inclusion criteria, public data sources, and procedures for linking across sources are described in the manuscript. Personal identifiers for researchers have been anonymized, but remain consistent across all data in the repository. In other words, the personal identifier "1" refers to the same person in all dataframes in the repository. But, that person is *not* the same researcher identified as "1" on the public AFT website.</p> <p><strong>Installation</strong></p> <p>Requires Python 3.x. and Pandas. To load required libraries using Anaconda, run:</p> <p>`conda create --name aft -c conda-forge pandas numpy scipy ipython jupyterlab scipy scikit-learn pandas matplotlib numpy statsmodels seaborn pytables`</p> <p><strong>Dataframes</strong></p> <p>Data is stored as a series of Pandas dataframes within HDF5 or CSV files:</p> <p>* cng_tc: The primary dataset used in the analysis. The name is an acronym for "connections" (i.e. training relationships, "cn"), "gender" ("g"), and "trainee count" ("tc"). Each row contains data on the mentor and trainee in one training relationship. See manuscript for inclusion criteria.</p> <p>* mentors: Data on mentors. Each row contains data on one mentor. See manunscript for inclusion criteria.</p> <p>* mentors_grants, mentors_hindex, mentors_locs_ranked: Subset of mentors with data available for funding (mentors_grants), citation (mentors_hindex), and institution rank (mentors_locs_ranked).</p> <p>* mentors_nobel, mentors_hhmi, mentors_nas: Subsets of mentors that received a Nobel (mentors_nobel), Howard Hughes Medical Institute grants (mentors_hhmi), or membership in the National Academy of Sciences (mentors_nas). See manuscript for details of data sources and linking procedures.</p> <p>* cn, cng, first_names, gn, gn_all, locs: Partial data (connections only, inferred gender only, connections and gender only, location only, first names and inferred gender only) for more inclusive sets of researchers in AFT. They are generally not used used for analysis, but have been included here to calculate statistics on the total amount of data included and to screen for data from U.S. locations.</p> <p>* nsf_gender_phds, nsf_gender_pds: National Science Foundation survey data on gender and fraction PhDs conferred per year (nsf_gender_phds) or fraction postdocs employed per year (nsf_gender_pds). See manuscript for details of data source.</p> <p>* photo: Data for validation of gender inference method.</p> <p><strong>Dataframe columns</strong></p> <p>* amount: Mentor's total funding<br> * amount_adj: Mentor's total funding (adjusted to 2020 dollars)<br> * broad_field: Mentor's general research area (e.g., life sciences, engineering, based on National Science Foundation classifications)<br> * continue: Whether trainee went on to become a mentor (i.e., has trainees listed in AFT)<br> * country: Country in which mentor's current institution is located<br> * firstname: First name of researcher (table of first names is not aligned with tables containing anonymized personal identifiers)<br> * first_grant_year: Year of mentor's first grant<br> * funding_rate: Mentor's annual funding rate (since first grant)<br> * funding_rate_adj: Mentor's annual funding rate (since first grant) adjusted to 2020 dollars<br> * hhmi: Whether mentor was granted HHMI funding<br> * hindex: Mentor's hindex<br> * location: Name of mentor's current institution<br> * locid: Identifier for mentor's institution<br> * locid_rank: Postion of mentor's institution in 2015 Quacquarelli-Symonds rankings (lower numbers are better)<br> * locid_rank_rev: Reversed version of "locid_rank" (i.e., higher numbers are better)<br> * majorarea: Mentor's specific research area (e.g, neuroscience)<br> * male_mentor, male trainee: Whether the probability that a researcher's first name is used by a person identifying as a man meets threshold (see manuscript for details on gender inference using first names)<br> * match_score: Score for string match between institution or name of awardee and researcher<br> * mentor_career_start: The date at which the mentor's academic career began<br> * mentor_continue_rate: Fraction of mentor's trainees that become mentors<br> * mentor_continue_rate_ft: Fraction of mentor's woman trainees that become mentors<br> * mentor_continue_rate_mt: Fraction of mentor's man trainees that become mentors<br> * mentor_t_p_male0: Fraction of mentor's trainees that are men<br> * mentor_t_p_male0_gs: Fraction of mentor's trainees that are men (graduate students only)<br> * mentor_t_p_male0_pd: Fraction of mentor's trainees that are men (postdocs only)<br> * mentor_tcount0: Mentor's total number of trainees<br> * nas: Whether mentor is a member of the National Academy of Sciences<br> * nobel: Whether mentor is a Nobel laureate<br> * p_male_mentor, p_male_trainee: Probability that a researcher's first name is used by a person identifying as a man<br> * pid: Anonymized identifier of researcher<br> * pid_mentor: Anonymized identifier of mentor in training relationship<br> * pid_trainee: Anonymized identifier of trainee in training relationship<br> * pq: "1" if data on training relationship is drawn from ProQuest database and has not been manually edited a human AFT user<br> * relation: Type of training relationship (1: graduate student, 2: postdoc)<br> * scorer1, scorer2, scorer3: Results of photo validation of gender inference for each scorer<br> * start: Training start year<br> * stop: Training end year<br> * trainee_tcount: Total people that the trainee has trained<br> * triad: Whether trainee has participated in both a graduate-level and postdoctoral training relationship</p> <p>The cn dataframe follows slightly different naming conventions, but is not generally used in the analysis (pid1 = pid_trainee, pid2 = pid_mentor, startdate = start, stopdate = stop).</p>
The cost of self-promotion: Ecological and demographic implications of the mentor effect in natural Taraxacum populations
<p>This data accompanies the pending publication "The cost of self-promotion: Ecological and demographic implications of the mentor effect in natural <em>Taraxacum </em>populations" by Lynn et al. The work is also published under Austin Lynn's PhD Dissertation, which is under embargo until 2022.</p>
Data from evaluation of the WHO ICFP2022 Scientific Writing, Mentoring and Coaching Course
<p>Data from the evaluation of the WHO ICFP 2022 scientific writing, mentoring and coaching course.</p> <ol> <li>Dataset includes responses from 49 participants and 12 coaches who responded to a questionnaire about their experience and engagement with the post conference coaching course</li> <li>Dataset includes responses from participants and mentors who attended the ICFP2022 in-conference workshop and mentoring program</li> </ol>
Data for: Two-Sided Matching for mentor-mentee allocations - Algorithms and manipulation strategies
<p>These are the data files for the PLOS ONE journal article "Two-Sided Matching for mentor-mentee allocations - Algorithms and manipulation strategies".</p> <p>Three files are provided:</p> <p>- Data.xlsx: An overview of the original preferences of mentors and mentee, a data dictionary, and two summary tables used to create figures in the manuscript</p> <p>- MatchingTables.csv: The outcome matching tables for each simulated scenario and repetition</p> <p>- Preferences.csv: The (un)manipulated preferences that were used as input to calculate the solution for each simulated scenario and repetition.</p>
Fig. 34 in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 34. Ozzy Osbourne meets Elvis Presley. My all-time favourite photo of Bill and I (Photo: John Measey).
Fig. 35 in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 35. Bill emerging from swamp in Gabon (2002) after checking funnel traps that he had set with the hope of catching an African Parachanna (Photo: Marius Burger).
Fig. 20 in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 20. Bill Branch and Mark-Oliver Rödel in July 2018 in Bill's home in Port Elizabeth (Photo: Mark-Oliver Rödel).
Fig. 16 in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 16. Bill Branch discussing the finer points of the day's photographic record of collections with colleagues and students, Lagoa Carumbo, May 2012. (Photo: Brian Huntley).
Fig. 12 in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 12. Michael Bates (left) with Bill Branch and Darren Pietersen during the Herpetological Association of Africa's conference in Pretoria in 2013 (Photo: W.R. Schmidt).
Fig. 10 in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 10. The Mt. Mabu 2009 science team. Left to right: Werner Conradie, Martin Hassan, Julian Bayliss, Bill Branch, Hassam Patel, Colin Congdon, and Steve Collins (Photo: Julian Bayliss).
Fig. 8. Taking a in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 8. Taking a "selfie" with Bill as part of the prize for runner-up best photographer (Photo: Shivan Parusnath).
Fig. 33. 2017 in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 33. 2017 Herpetological Association of Africa's Conference in Bonamanzi, South Africa. From left to right: Werner Conradie, Tyrone Ping, Prof. William Branch, Luke Verburgt, Dr. Michael Bates, Johan Marais, Prof. Graham Alexander, Prof. Aaron Bauer, Jens Reissig, Coleen Tiedemann, Dr. Colin Tilbury, and Dr. Victor Loehr (Photo: Andre Coetzer).
Fig. 9 in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 9. Photograph of Atheris mabuensis taken by Bill― probably the best photograph of a snake I have ever seen (Photo: Bill Branch).
Fig. 38. Bill holding a in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 38. Bill holding a Meller's Chameleon (Trioceros melleri), looking radiant despite a very tiring hike during the summit of Mt. Mabu in 2009 (Photo: Werner Conradie).
Fig. 6 in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 6. Male New Caledonian Geckos (Rhacodactylus leachianus) still alive in Port Elizabeth Snake Park (Photo: Werner Conradie).
Fig. 7 in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 7. Varanid Symposium participants at Museum Alexander Koenig in 1991. Bill Branch is the seventh person from the left, in the front row.
Fig. 5 in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 5. Jonno Webb, Bill Branch, and Peter Harlow posing at the outskirts of the town of Poffadder in northern South Africa, reveling in the idea that somebody actually named a town after a snake (Photo: Rick Shine).
Fig. 1 in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 1. Cover image of Hyperolius raymondi used for Frogs and other Amphibians of Africa (Photo: Bill Branch).
Fig. 3. Bill Xerox-ing a in Compilation of personal tributes to William Roy Branch (1946-2018): a loving husband and father, a good friend, and a mentor
Fig. 3. Bill Xerox-ing a puffadder to make counting of scales easier, to the disgrace of the librarian (Photo: Dot Pitman).
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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International Brain Laboratory public data
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OpenNeuro
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