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Record W4389487320 · doi:10.18535/ijsrm/v11i12.lla02

Characteristics, Roles and Challenges of Traffic Personnel: Implications toward Efficient Traffic Management System

2023· article· en· W4389487320 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Scientific Research and Management (IJSRM) · 2023
Typearticle
Languageen
FieldEngineering
TopicUrban Transport Systems Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)IBMPsychologyNonprobability samplingTraffic policeThematic analysisQualitative propertyOperations managementApplied psychologyMedical educationBusinessQualitative researchEngineeringSociologyMedicineStatisticsGeographyDemographyNursingSocial scienceMathematics

Abstract

fetched live from OpenAlex

The purpose of this study was to determine the characteristics, roles and challenges of traffic personnel and their implications toward efficient traffic management system in Bacolod City during the second quarter of calendar year 2018. A mixed methods research design was used which involved the use of both quantitative and qualitative methods by means of survey responded by 150 traffic personnel, key informant interview participated by 3 Barangay Captains and a City Councilor, and focus group discussion participated by 6 traffic personnel which were all selected through a purposive and convenience sampling techniques. Frequency count, percentage, weighted mean, standard deviation, Mann- Whitney U, Kruskal Wallis and IBM SPSS Version 19 were employed to analyze and present the data for quantitative part. While the qualitative part of the study, Thematic Analysis was utilized. The findings showed that traffic personnel who participated in the study were almost equally divided when grouped according to age, while majority were male, attained college level, have less than 7 years of experience and designated as traffic enforcer. Meanwhile, not all completed the required trainings. When it comes to their roles as traffic personnel, it showed that they are mainly managing traffic flow and implementing traffic rules and regulations in the roads. Moreover, it showed that majority of them are highly knowledgeable on City Ordinance 338, and there are no significant differences when they were grouped according to age, sex, educational attainment, and job designation. However, significant differences were found in their level of knowledge on the aforementioned ordinance when they were grouped according to length of service and trainings attended. On the other hand, it was found out that the top most challenge experienced by the participants is the arrogance of drivers. The lack of discipline which includes disregarding of traffic rules and regulations among drivers follows next. Ignorance of the traffic rules and regulations among road users, attitude of drivers, bad weather conditions, high volume of vehicles and road widening projects are also included in the short list of challenges encountered by traffic personnel in the City. Finally, results of this study were used in formulating an enhanced traffic management system program for Bacolod Traffic Authority Office.

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.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.292
Teacher spread0.231 · 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