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Record W2622009571

Working Anytime Anywhere: Mobile Knowledge Workers

2014· other· en· W2622009571 on OpenAlexaboutno aff
Cheuk Ng

Bibliographic record

VenueAUSpace (Athabasca University) · 2014
Typeother
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsPresentation (obstetrics)CommodificationSocial mediaPublic relationsSociologyStewardship (theology)Theme (computing)Media studiesWork (physics)PoliticsPolitical scienceWorld Wide WebEngineeringComputer scienceMedicine
DOInot available

Abstract

fetched live from OpenAlex

I made the presentation entitled “Mobile knowledge workers working anytime anywhere?” to an audience with various disciplinary backgrounds from around the world at the 2nd World Social Sciences Forum in Montreal, Quebec, on October 15, 2013. The theme of the Forum was Social Transformations and the Digital Age, covering a wide range of topics such as big/open data, research libraries’ role in data stewardship, intergenerational communication, and privacy and surveillance. My presentation was part of a symposium on New Forms of Work. The other presentations at the symposium ranged from understanding work, family, and technology figurations in the home, corporate crisis management in times of social media, to immaterial labour, monetization, commodification and the political in social media. The international audience showed general interest in telework and mobile work as changes in the world of work. My presentation was received well, with several colleagues sharing related work or requesting for a copy of my presentation and related papers for use in their teaching and research. Participation in other sessions at the Forum provided further food for thought for my teaching and research as our society is being transformed in many ways in this digital age.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.064
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.012
GPT teacher head0.230
Teacher spread0.217 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2014
Admission routes1
Has abstractyes

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