You are a brand: social media managers’ personal branding and “the future audience”
Bibliographic record
Abstract
Purpose: Social media management is an emerging profession that is growing as companies increasingly adopt social media. The purpose of this paper is to analyze social media managers’ personal branding. Design/methodology/approach: In-depth qualitative data is drawn from 20 semi-structured interviews with social media managers and supported by three years of orienting fieldwork in Toronto, Canada. Findings: Social media managers are responsible for managing and executing organizations’ brands and presence on social media and digital platforms. As lead users of social media, social media managers provide critical insight into the emerging practices of personal branding on social media. “The future audience” is introduced to describe how individuals project a curated brand for all future unknown and unanticipated audiences, which emphasizes a professional identity. Due to workplace uncertainty, social media managers embody the mentality of being “always-on-the-job-market”, which is a driver for personal branding in their attempt to gain or maintain employment. Originality/value: While personal branding is largely discussed by industry professionals, there is a need for empirical research on personal branding that examines how various employee groups experience personal branding. This research fills this gap by analyzing how people working in social media brand their identity and how their personal branding is used to market themselves to gain and maintain employment. The development of “the future audience” and “always-on-the-job-market” can be used to understand other professions and experiences of personal branding.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".