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Record W1565675407 · doi:10.1044/leader.gs.20032015.np

Using Social Media for Professional Advancement: Lessons Learned

2015· article· en· W1565675407 on OpenAlexaboutno aff
Tanya Coyle, Mai Ling Chan

Bibliographic record

VenueASHA Leader · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsnot available
Fundersnot available
KeywordsAmerican Speech-Language-Hearing AssociationSocial mediaPsychologyMedical educationProfessional developmentPedagogyMedicineComputer scienceLinguisticsWorld Wide WebAsha

Abstract

fetched live from OpenAlex

You have accessThe ASHA LeaderGet Social1 Mar 2015Using Social Media for Professional Advancement: Lessons LearnedSee how peers use Twitter, Facebook, Instagram, Pinterest and more to improve clinical skills, interact with colleagues, share insights and discover the latest research. Tanya Coyle, andMSc, S-LP(C) Mai Ling ChanMS, SLP Tanya Coyle Google Scholar , MSc, S-LP(C) and Mai Ling Chan Google Scholar , MS, SLP https://doi.org/10.1044/leader.GS.20032015.np SectionsAbout ToolsAdd to favorites ShareFacebookTwitterLinked In If you’re interested in using social media professionally but haven’t been following the column so far, take a moment to catch up. Read on for professional social media 101: a roundup of previous articles written by active members of our socmed (social media) community. In our first column, we introduce you to what social media is and how some people conceptualize its use in the field. We liken it to one large and globally extending conference that never ends. We discuss how communicative disorders professionals are using various platforms such as Facebook, Twitter, Pinterest, blogs, and even Instagram. In case you want even more, there’s an article summarizing socmed platforms again and citing many ways in which to connect with ASHA and National Student Speech-Language Hearing Association by using them. The column also includes articles on how professionals incorporate social media into their practice. We advise that you don’t have to feel obliged to interact on these platforms and can benefit by just reading, although you’ll miss the opportunity for networking. And your peers already on social media are very willing to interact with you if you want. In addition, we share how professionals of all ages use social media and that there are ways to keep your personal life separate from your professional social media use. Now, let’s talk about a great trend in social media that we haven’t yet covered: Research Tuesday! Ian A. Elliott, a visiting assistant professor in the University of Massachusetts Lowell’s criminal justice department, first used #ResearchTues in November 2012. He reports he “had a backlog of journal alerts at that time” and “decided to set aside an hour every Tuesday to go through them and used #ResearchTues as a way to mentally keep myself on schedule.” Rachel Wynn, SLP and author/blogger of Gray Matter Therapy, began using this hashtag a year later and has since shaped this conversation into a more consistent and focused community. She invites bloggers and tweeters to “write about recent research that applies to their therapy practice” every second Tuesday of the month. This is well received in the communicative disorders twittersphere, as evidenced by the steady stream of tweets linking to research-relevant blogs and comments, as well as ASHA’s official adoption of the practice in December 2014. Specific details on how #ResearchTues works are available on Rachel’s blog. We hope you find this information helpful while you navigate available online communities. There’s more to come throughout this year. We will discuss how to use social media to find information, join conversations and share ideas about specific topics in speech pathology and audiology. Author Notes Tanya Coyle, MSc, S-LP(C), is a school-based SLP in Ontario, Canada who helped establish the speech-language community on Twitter in 2010. She has also authored speech-language and educational apps for iPad and is co-founder and director of social media for YappGuru Mai Ling Chan MS, SLP, is an Arizona based clinician, is co-founder and ceo of YappGuru where she provides consulting, training and collaboration to other industry experts to promote mobile technology integration into special education and rehabilitation. Advertising Disclaimer | Advertise With Us Advertising Disclaimer | Advertise With Us Additional Resources FiguresSourcesRelatedDetails Volume 20Issue 3March 2015 Get Permissions Add to your Mendeley library History Published in print: Mar 1, 2015 Metrics Current downloads: 322 Topicsasha-topicsleader_do_tagleader-topicsasha-article-typesCopyright & Permissions© 2015 American Speech-Language-Hearing AssociationLoading ...

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)0.022
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.030
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0040.005
Scholarly communication0.0110.022
Open science0.0030.007
Research integrity0.0070.012
Insufficient payload (model declined to judge)0.0130.007

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 head0.400
GPT teacher head0.497
Teacher spread0.097 · 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 designQualitative
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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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