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Record W2595633500 · doi:10.7939/r3db7vr97

Use of online social media networking sites: An exploration of the impact on a major law enforcement agency

2014· article· en· W2595633500 on OpenAlexaboutno aff
Shantel Mackenzie-McDonald

Bibliographic record

VenueUniversity of Alberta Library · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicStalking, Cyberstalking, and Harassment
Canadian institutionsnot available
Fundersnot available
KeywordsSocial mediaLaw enforcementPopularityAgency (philosophy)Public relationsExploratory researchEnforcementInternet privacyBusinessPsychologyPolitical scienceSociologySocial psychologyLawComputer science

Abstract

fetched live from OpenAlex

The popularity of social media sites has grown exponentially over the past few years. However there is limited research regarding the impact that online social media networking sites have on a major law enforcement agency. This study investigates whether the use of online social media networking sites impact the actions and behaviors of police officers within the Edmonton Police Service (EPS). Six participants from the EPS were interviewed for this research project using a semi-structured, in-person interview methodology. Findings were analyzed under an exploratory approach in order to determine the connection between social media sites and the impacts on the individual participants interviewed. The results of this study find that online social media networking sites do have a direct impact on the actions and behaviours of police officers. The study identified three distinct themes; 1 – the police value social media as an investigative tool and communication channel, 2 – the general public’s use of social media sites are predominately used negatively toward the police, and 3 – some police officers intentionally alter their actions or behaviours due to the high probability of being captured on video. An awareness and understanding of the use of online social media networking sites, by the police and the general public, highlight the impacts on the behaviours and actions of police officers within the EPS.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.060
GPT teacher head0.273
Teacher spread0.213 · 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 teacher head, 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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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