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These datasets are derived from the boundaries of the Barangays as observed at the end of April 2016 as per the Philippine Geographic Standard Code (PSGC) dataset. It has been generated on the basis of the layer created by the Philippine Statistics Authority (PSA) in the context of the 2015 population census. These datasets have been vetted by staff at The Carl Vinson Institute of Government's Office of Information Technology Outreach Services (ITOS) according to their COD assessment protocol found in the COD Technical Support Package (https://sites.google.com/site/commonoperationaldataset/geodata-preparation-manual/itos-process).
Acknowledge PSA and NAMRIA as the sources. LMB is still the source of official administrative boundaries of the Philippines. In the absence of available official administrative boundary, the IMTWG have agreed to clean and use the PSA administrative boundaries which are used to facilitate data collection of surveys and censuses. The dataset can only be considered as indicative boundaries and not official. * For administrative level 4 (Barangay) please contact the contributor (OCHA Philippines) via this page. This COD replaces https://data.humdata.org/dataset/philippines-administrative-boundaries

Philippines administrative levels:

(0) Country

(1) Region (Filipino: rehiyon)

(2) Provinces (Filipino: lalawigan, probinsiya) and independent cities (Filipino: lungsod, siyudad/ciudad, dakbayan, lakanbalen)

(3) Municipalities (Filipino: bayan, balen, bungto, banwa, ili) and component cities (Filipino: lungsod, siyudad/ciudad, dakbayan, dakbanwa, lakanbalen)

These shapefiles are suitable for database or ArcGIS joins to the sex and age disaggregated population statistics found on HDX here.

7-day daily fire potential forecast by predictive service area (PSA), with each day as its own layer. The current day is Day 1.(PSA shapefile source: https://data-nifc.opendata.arcgis.com; updated 18 January 2023. Note: Updated PSA geometry and attributes are reflected in this product as of 2 February 2023.)Data Source National Interagency Fire Center / Predictive Services ProgramUpdate Frequency DailyDataset Link Polygon ShapefileMore Data and services at NATIONAL 7-DAY SIGNIFICANT FIRE POTENTIAL download page

The organic molecular porous material 1 obtained by recrystallization of cucurbit[6]uril (CB[6]) from HCl shows a high CO2 sorption capacity at 298 K, 1 bar. Most interestingly, 1 showed the highest selectivity of CO2 over CO among the known porous materials so far. The remarkable selectivity of CO2 may be attributed to the exceptionally high enthalpy of adsorption (33.0 kJ/mol). X-ray crystal structure analysis of CO2 adsorbed 1 revealed three independent CO2 sorption sites: two in the 1D channels (A and B) and one in the molecular cavities (C). The CO2 molecules adsorbed at sorption site A near the wall of the 1D channels interact with 1 through hydrogen bonding and at the same time interact with those at site B mainly through quadrupole−quadrupole interaction in a T-shaped arrangement. Interestingly, two CO2 molecules are included in the CB[6] cavity (site C), interacting not only with the carbonyl groups of CB[6] but also with each other in a slipped-parallel geometry. The exceptionally selective CO2 sorption properties of 1 may find useful applications in the pressure swing adsorption (PSA) process for CO2 separation not only in the steel industry but also in other industries such as natural gas mining.

Abstract

The 2022 Philippines National Demographic and Health Survey (NDHS) was implemented by the Philippine Statistics Authority (PSA). Data collection took place from May 2 to June 22, 2022.

The primary objective of the 2022 NDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the NDHS collected information on fertility, fertility preferences, family planning practices, childhood mortality, maternal and child health, nutrition, knowledge and attitudes regarding HIV/AIDS, violence against women, child discipline, early childhood development, and other health issues.

The information collected through the NDHS is intended to assist policymakers and program managers in designing and evaluating programs and strategies for improving the health of the country’s population. The 2022 NDHS also provides indicators anchored to the attainment of the Sustainable Development Goals (SDGs) and the new Philippine Development Plan for 2023 to 2028.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling scheme provides data representative of the country as a whole, for urban and rural areas separately, and for each of the country’s administrative regions. The sample selection methodology for the 2022 NDHS was based on a two-stage stratified sample design using the Master Sample Frame (MSF) designed and compiled by the PSA. The MSF was constructed based on the listing of households from the 2010 Census of Population and Housing and updated based on the listing of households from the 2015 Census of Population. The first stage involved a systematic selection of 1,247 primary sampling units (PSUs) distributed by province or HUC. A PSU can be a barangay, a portion of a large barangay, or two or more adjacent small barangays.

In the second stage, an equal take of either 22 or 29 sample housing units were selected from each sampled PSU using systematic random sampling. In situations where a housing unit contained one to three households, all households were interviewed. In the rare situation where a housing unit contained more than three households, no more than three households were interviewed. The survey interviewers were instructed to interview only the preselected housing units. No replacements and no changes of the preselected housing units were allowed in the implementing stage in order to prevent bias. Survey weights were calculated, added to the data file, and applied so that weighted results are representative estimates of indicators at the regional and national levels.

All women age 15–49 who were either usual residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. Among women eligible for an individual interview, one woman per household was selected for a module on women’s safety.

For further details on sample design, see APPENDIX A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Two questionnaires were used for the 2022 NDHS: the Household Questionnaire and the Woman’s Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to the Philippines. Input was solicited from various stakeholders representing government agencies, academe, and international agencies. The survey protocol was reviewed by the ICF Institutional Review Board.

After all questionnaires were finalized in English, they were translated into six major languages: Tagalog, Cebuano, Ilocano, Bikol, Hiligaynon, and Waray. The Household and Woman’s Questionnaires were programmed into tablet computers to allow for computer-assisted personal interviewing (CAPI) for data collection purposes, with the capability to choose any of the languages for each questionnaire.

Cleaning operations

Processing the 2022 NDHS data began almost as soon as fieldwork started, and data security procedures were in place in accordance with confidentiality of information as provided by Philippine laws. As data collection was completed in each PSU or cluster, all electronic data files were transferred securely via SyncCloud to a server maintained by the PSA Central Office in Quezon City. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors while still in the area of assignment. Timely generation of field check tables allowed for effective monitoring of fieldwork, including tracking questionnaire completion rates. Only the field teams, project managers, and NDHS supervisors in the provincial, regional, and central offices were given access to the CAPI system and the SyncCloud server.

A team of secondary editors in the PSA Central Office carried out secondary editing, which involved resolving inconsistencies and recoding “other” responses; the former was conducted during data collection, and the latter was conducted following the completion of the fieldwork. Data editing was performed using the CSPro software package. The secondary editing of the data was completed in August 2022. The final cleaning of the data set was carried out by data processing specialists from The DHS Program in September 2022.

Response rate

A total of 35,470 households were selected for the 2022 NDHS sample, of which 30,621 were found to be occupied. Of the occupied households, 30,372 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 28,379 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 27,821 women, yielding a response rate of 98%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and in data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2022 Philippines National Demographic and Health Survey (2022 NDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2022 NDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2022 NDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Household age distribution
• Age distribution of eligible and interviewed women
• Age displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Observation of handwashing facility
• School attendance by single year of age
• Vaccination cards photographed
• Population pyramid
• Five-year mortality rates

See details of the data quality tables in Appendix C of the final report.

Abstract

The Republic of the Philippines is making great efforts to develop agriculture at a pace necessary to meet the food requirements of the fast-growing population. It has become necessary to use current agricultural statistics that will help present an accurate picture of the country's food situation. Especially important are the expected supply and consumption requirements of the people, particularly of meat products. The Commercial Livestock and Poultry Survey (CLPS) seeks to provide if but partially, such information.

The CLPS is one of the major regular activities of the Livestock and Poultry Statistics Division (LPSD) under the Economic Sector Statistics Service (ESSS) of the Philippine Statistics Authority (PSA). The CLPS is undertaken to provide an estimate on current inventory and supply and disposition of commercial livestock and poultry farms. The CLPS is done quarterly for swine, broiler, and layer while data collection for carabao, cattle, goat, duck and sheep is likewise conducted semi-annually. The information present here is related to the layer module.

The survey covers all provinces including Dinagat Islands and two (2) chartered cities (Davao City and Zamboanga City). Moreover, a separate structured questionnaire in the collection of the necessary information for each animal type is utilized. Estimates generated from the CLPS and the Backyard Livestock and Poultry Survey (BLPS) are aggregated to come up with the total Livestock and Poultry (L&P) estimates. The data generated was perceived to be useful as guide for the government and the private sector in making plans and decisions with respect to farm production and improvement of the livestock and poultry industry.

The data generated from this survey are disseminated through the country STAT website and featured in the Quarterly Commodity Special Releases and Annual Commodity Situation Reports released every May. The collection of data on this survey is undertaken by hired Statistical Researchers (SRs) while the electronic processing is done by the regular staff in the Provincial Statistical Offices (POs). The SRs are trained prior to field operations to ensure that the procedures and concepts are understood. The training includes mock interviews and dry-run exercises.

Geographic coverage

National Coverage

Analysis unit

Entreprises

Universe

The CLPS covers all livestock and poultry farms with commercial type of operation. Commercial farm refers to a farm or household operated by a farmer/household/operator that raises at least one of the following: 1. Livestock - Carabao (Water Buffaloes), Cattle, Swine and Goat 2. Poultry - Layer, Broiler and Duck

Also, it must satisfy at least one of the following criteria: 1. Livestock · at least 21 heads of adult and zero head of young · at least 41 heads of young animals and above · at least 10 heads of adult and 22 heads of young and above

1. Poultry · at least 500 layers, or 1,000 broilers and above · at least 100 layers and 100 broilers if raised in combination and above · at least 100 head of duck regardless of age

The survey also covers traders such as assemblers and distributors, etc.

Trader refers to a person or entity that buys and sells goods or commodities.

Assembler refers to a type of trader who sources and procures his/her stocks from contract growers or independent farmers in several barangays in a specific municipality, and transports the produce to a trading or market center.

Distributor refers to a trader who sells commodities to other traders and consumers.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE SELECTION PROCEDURE The sampling design used for each animal type are the same but are treated independently. The sampling design depends on the total number of commercial farms and the corresponding maximum housing capacities of the farms in the province. In provinces with less than 21 farms, all farms are completely enumerated. However, provinces with a large number of farms or those with 21 or more farms, stratification is applied using the Dalenius-Hodges method of stratification with the maximum housing capacity as stratification variable. The number of strata per province ranges from two (2) to four (4) depending on the heterogeneity or homogeneity of the maximum housing capacity. Sample allocation for each stratum is done using the Neyman procedure with coefficient of variation set at five percent (5%). A minimum of five (5) samples per stratum is allocated. A stratum may have less than 5 samples only if the total number of farms in that stratum is less than 5. Selection of samples from each stratum is done using simple random sampling.

The sample selection procedure is discussed as follows: 1. Rank all farms in ascending order according to their maximum housing capacity; 2. Delineate the stratum boundaries using Dalenius-Hodges method (unique stratum boundaries for each province are derived); 3. Determine the total number of commercial farms per stratum; 4. Allocate sample size for each stratum using Neyman procedure (a five percent (5%) coefficient of variation is assumed and a minimum of five (5) samples are taken when Nh = 5). For stratum with Nh<5, all farms in that stratum shall be enumerated; and 5. Select the required number of sample farms using the simple random sampling method.

For provinces where stratified sampling is employed, in case of non-response, adjustment of expansion factor is implemented by stratum and by animal type using the status of the sample commercial farms.

Comprehensive discussion on the estimation procedure is found in page 10 of the CLPS manual found in Related Materials.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

For CLPS, editing is done in two (2) stage. The first stage of editing is done during the data collection. The Statistical Researcher, before leaving the premises of the sample commercial farm, shall do field editing. This activity involves assuring that all data items in the questionnaires are asked and that the answers were written down correctly. The second stage of editing is conducted by the supervisor upon the submission of accomplished questionnaires/forms by the SR called manual editing.

The system used in processing the data collected from this survey was developed by the Systems Development Division (SDD) of PSA. CSPro, the software used in most of the surveys of PSA, is utilized.

Using a pre-formatted template, consolidated estimates are generated through the Provincial Summary Worksheets (PSW-C). This worksheet presents data for each sample commercial farm, raw provincial total data and expanded provincial total estimates.

These estimates are transferred manually into an excel-based validation sheet called the "Supply-Disposition Worksheets" where the PSO, together with the L&P focal person, act as data analysts. To ensure the quality of data, the generated outputs shall undergo data review and validation. Data review involves internal checks of the data collected, consistency and completeness check of data items and detection and correction of identified errors. Data validation, on the other hand, ensures that the estimates generated are truly reflective of the current industry situation. It involves a thorough analysis of the generated estimates using auxiliary information. Auxiliary information includes animal dispersal from government programs, weather condition, price trends, import and export among others. Data review and validation is supported by the Electronic Data Review Workbook (EDRW) Compilation System. This is a tool used in reviewing and validating the L&P statistics and commonly termed as "Supply-Disposition (S-D) Technique".

The outputs of the CLPS together with BLPS undergo three (3) levels of data review and validation. The first stage is at the Provincial level known as the Provincial Data Review (PDR) followed by the second level which takes place at the RSSOs, known as the Regional Data Review (RDR). During the RDR, the RSSOs shall likewise review and validate the outputs of the provinces under its jurisdiction.

The third level of data review and validation and is the final level is conducted at the Central Office. All outputs sent by the RSSOs shall be consolidated by the LPSD commodity specialists to generate the final livestock and poultry statistical tables as input in the preparation of reports.

Response rate

The response rate for the survey ranged from 85-90%.

Data appraisal

To ensure the quality of its statistical services, the PSA has mainstreamed in its statistical system for generating production statistics, a quarterly data review and validation process. This is undertaken at the provincial, regional and national levels to incorporate the impact of events not captured in the survey. The data review process starts at the data collection stage and continues up to the processing and tabulation of results. However, data examination is formalized during the provincial data review since it is at this stage where the data at the province-level is analyzed as a whole. The process involves analyzing the survey data in terms of completeness, consistency among variables, trend and concentration of the data and presence of extreme observations. Correction of spotted errors in the data is done afterwards. The output of the process is a clean data file used in the re-computation of survey estimates. The estimates generated from the clean data set are thoroughly analyzed and validated with auxiliary information to incorporate the impact of information and events not captured by the survey. This

This study was designed to analyze the impact of four televised public service announcements (PSAs) aired for three months in Lima, Ohio. The researchers sought to answer three specific research questions: (1) Were the PSAs effective in transferring knowledge to citizens about the police? (2) Did the PSAs have an impact on resident satisfaction with the police? and (3) Did the PSAs have an impact on the behavior of citizens interacting with the police? To assess public attitudes about the Lima police and to determine whether the substance of the PSAs was being communicated to the residents of Lima, three waves of telephone interviews were conducted (Part 1). The first telephone interviews were conducted in April 1996 with approximately 500 randomly selected Lima residents. These were baseline interviews that took place before the PSAs aired. The survey instrument used in the first interview assessed resident satisfaction with the police and the services they provided. After completion of the Wave 1 interviews, the PSAs were aired on television for three months (June 5-August 28, 1996). After August 28, the PSAs were removed from general circulation. A second wave of telephone interviews was conducted in September 1996 with a different group of randomly selected Lima residents. The same survey instrument used during the first interviews was administered during the second wave, with additional questions added relating to whether the respondent saw any of the PSAs. A third group of randomly selected Lima residents was contacted via the telephone in January 1997 for the final wave of interviews. The final interviews utilized the identical survey instrument used during Wave 2. The focus of this follow-up survey was on citizen retention, over time, of the information communicated in the PSAs. Official data collected from computerized records maintained by the Lima Police Department were also collected to monitor changes in citizen behavior (Part 2). The records data span 127 weeks, from January 1, 1995, to June 7, 1997, which includes 74 weeks of pre-PSA data and 53 weeks of data for the period during the initial airing of the first PSA and thereafter. Variables in Part 1 include whether respondents were interested in learning about what to do if stopped by the police, what actions they had displayed when stopped by the police, if they would defend another person being treated unfairly by the police, how responsible they felt (as a citizen) in preventing crimes, the likelihood of calling the police if they were aware of a crime, perception of crime and fear of crime, and whether there had been an increase or decrease in the level of crime in their neighborhoods. Respondents were also asked about the amount of television they watched, whether they saw any of the public service announcements and if so to rate them, whether the PSAs provided information not already known, whether any of the PSA topics had come up in conversations with family or friends, and whether the respondent would like to see more PSAs in the future. Finally, respondents were asked whether the police were doing as much as they could to make the neighborhood safe, how responsive the police were to nonemergency matters, and to rate their overall satisfaction with the Lima Police Department and its various services. Demographic variables for Part 1 include the race, gender, age, marital status, level of education, employment status, and income level of each respondent. Variables in Part 2 cover police use-of-force or resisting arrest incidents that took place during the study period, whether the PSA aired during the week in which a use-of-force or resisting arrest incident took place, the number of supplemental police use-of-force reports that were made, and the number of resisting arrest charges made.

Abstract

The Occupational Wages Survey (OWS) generates statistics for wage and salary administration and for wage determination in collective bargaining negotiations. This nationwide biennial survey covers establishments employing at least 20 workers.

The OWS is one of the designated statistical activities in E.O. 352 (s.1996) that designates those critical for decision making by the government and the private sector. Moreover, the data category average monthly occupational wage rates in selected occupation is among those listed by the Philippine government under the Special Data Dissemination Standard (SDDS) of the International Monetary Fund. The SDDS serves as reference to member countries in the dissemination of economic and financial data to the public.

Geographic coverage

National coverage, 17 administrative regions

Analysis unit

Establishment

Universe

The survey covers agricultural and non-agricultural establishments employing 20 or more workers except central banking, public administration and defense and compulsory social security, public education services, public medical, dental and other health services, activities of membership organizations, activities of households as employers of domestic personnel, undifferentiated goods-and-services-producing activities of households for own use and activities of extra-territorial organizations and bodies.

Pre-determined industries for wage monitoring now total to 50 due to the inclusion of agriculture, forestry and fishery; and the splitting and merging of original domains with the adoption of the 2009 PSIC.

Inclusion of new domains: - Crop and Animal Production, Hunting and Related Service Activities; Forestry and Logging (A01/A02) - Fishing and Aquaculture (A03) - Manufacture of Basic Pharmaceutical Products and Pharmaceutical Preparation (C21)

Splitting of original domains: - Publishing and Printing (D221/D222/D223 of 1994 PSIC as amended) into Printing and Reproduction of Recorded Media (C18); and Publishing Activities (J58) - Supporting and Auxiliary Transport Activities; Activities of Travel Agencies (I63 of 1994 PSIC as amended) into Warehousing and Support Activities for Transportation (H52); and Travel Agency, Tour Operator, Reservation Service and Related Activities (N79)

Merging of original domains: - Banking Institutions except Central Banking (J65 excl. J6510 of 1994 PSIC as amended) and Non-Bank Financial Intermediation (J66 of 1994 PSIC as amended) into Financial Service Activities except Insurance, Pension Funding and Central Banking (K64 excl. K6411)

Kind of data

Sample survey data [ssd]

Sampling procedure

Statistical unit: The statistical unit is the establishment. Each unit is classified to an industry that reflects its main economic activity---the activity that contributes the biggest or major portion of the gross income or revenues of the establishment.

Survey universe/Sampling frame: The 2014 BLES Survey Sampling Frame (2014 SSF) is an integrated list of establishments culled from the updated 2012 BLES Survey Sampling Frame based on the status of establishments reported in the 2011/2012 BLES Integrated Survey (BITS) and 2012 Occupational Wages Survey (OWS). Other sources were Lists of Establishments from the National Statistics Office (2012), DOLE Regional Office IV-B,and the BLES Job Displacement Monitoring System (JDMS).

Sampling design: The OWS is a sample survey of agricultural and non-agricultural establishments employing 20 persons or more where the survey domain is the industry. Those establishments employing at least 200 persons are covered with certainty and the rest are sampled (stratified random sampling). The design does not consider the region as a domain to allow for detailed industry groupings.

Sample size: For 2014 OWS, the number of establishments covered was 8,399, of which, 6,595 were eligible units.

Mode of data collection

Other [oth]

Research instrument

The questionnaire contains the following sections:

Cover Page (Page 1) This contains the address box, contact particulars for assistance, spaces for changes in the name and location of sample establishment and head office information in case the questionnaire is endorsed to it and status codes of the establishment to be accomplished by PSA and its field personnel.

Survey Information (Page 2) This contains the survey objective and uses of the data, scope of the survey, confidentiality clause, collection authority, authorized field personnel, coverage, periodicity and reference period, due date for accomplishment and expected date when the results of the 2014 OWS would be available.

Part A: General Information (Page 3) This portion inquires on main economic activity, major products/goods or services and total employment.

Part B: Employment and Wage Rates of Time-Rate Workers on Full-Time Basis (Pages 4-5) This section requires data on the number of time-rate workers on full-time basis by time unit and by basic pay and allowance intervals.

Part C: Employment and Wage Rates of Time-Rate Workers on Full-Time Basis in Selected Occupations (Pages 6-9) This part inquires on the basic pay and allowance per time unit and corresponding number of workers in the two benchmark occupations and in the pre-determined occupations listed in the occupational sheet to be provided to the establishment where applicable.

Part D: Certification (Page 10) This portion is provided for the respondent's name/signature, position, telephone no., fax no. and e-mail address and time spent in answering the questionnaire.

Appropriate spaces are also provided to elicit comments on data provided for the 2014 OWS; results of the 2012 OWS; and presentation/packaging, particularly on the definition of terms, layout, font and color.

Part E: Survey Personnel (Page 10) This portion is for the particulars of the enumerators and area/regional supervisors and reviewers at the PSA Central Office and PSA Field Offices involved in the data collection and review of questionnaire entries.

Part F: Industries With Selected Occupations (Page 11) The list of industries for occupational wage monitoring has been provided to guide the enumerators in ensuring that the correct occupational sheet has been furnished to the respondent.

Selected Statistics from 2012 OWS (Page 12) The results of the 2012 OWS are found on page 12 of the questionnaire. These results can serve as a guide to the survey personnel in editing/review of the entries in the questionnaire.

Cleaning operations

Data are manually and electronically processed. Upon collection of accomplished questionnaires, enumerators perform field editing before leaving the establishments to ensure completeness, consistency and reasonableness of entries in accordance with the field operations manual. The forms are again checked for data consistency and completeness by their field supervisors.

The LSRSD personnel undertake the final review, coding of information on classifications used, data entry and validation and scrutiny of aggregated results for coherence. Questionnaires with incomplete or inconsistent entries are returned to the establishments for verification, personally or through mail.

Response rate

The response rate in terms of eligible units was 87.2%.

Data appraisal

The survey results are checked for consistency with the results of previous OWS data and the minimum wage rates corresponding to the reference period of the survey.

Average wage rates of unskilled workers by region is compared for proximity with the corresponding minimum wage rates during the survey reference period.

Prostate cancer (PCa) patients undergoing androgen deprivation therapy almost invariably develop castration-resistant prostate cancer (CRPC). Targeting the androgen receptor (AR) Binding Function-3 (BF3) site offers a promising option to treat CRPC. However, BF3 inhibitors have been limited by poor potency or inadequate metabolic stability. Through extensive medicinal chemistry, molecular modeling, and biochemistry, we identified 2-(5,6,7-trifluoro-1H-Indol-3-yl)-quinoline-5-carboxamide (VPC-13789), a potent AR BF3 antagonist with markedly improved pharmacokinetic properties. We demonstrate that VPC-13789 suppresses AR-mediated transcription, chromatin binding, and recruitment of coregulatory proteins. This novel AR antagonist selectively reduces the growth of both androgen-dependent and enzalutamide-resistant PCa cell lines. Having demonstrated in vitro efficacy, we developed an orally bioavailable prodrug that reduced PSA production and tumor volume in animal models of CRPC with no observed toxicity. VPC-13789 is a potent, selective, and orally bioavailable antiandrogen with a distinct mode of action that has a potential as novel CRPC therapeutics.

Abstract

The Labor Force Survey (LFS) is a nationwide survey of households conducted quarterly to gather data on the demographic and socio-economic characteristics of the population. It is primarily geared towards the estimation of the levels of employment and unemployment in the country. One of the objectives of the Labor Force Survey is to provide a quantitative framework for the preparation of plans and formulation of policies affecting the labor market. Specifically, the survey is designed to provide statistics on levels and trends of employment, unemployment and underemployment of the country, as a whole, and for the 17 administrative regions.

A total national sample of 42,768 sample housholds (rounds with Batanes sample) or 42,576 sample households (rounds without Batanes sample) will be alloted per survey round deemed sufficient to provide more precise and reliable estimates at the national and regional levels only.

The survey involves the collection of data on demographic and socio-economic characteristics of the population in general. The reporting unit is the household which means that statistics emanating from this survey refers to the characteristics of the population residing in private households. Persons who belongs to the institutional population are not within the scope of the survey.

Geographic coverage

The sample was selected to allow separate estimates for the national level, and regional levels only (17 administrative regions).

National Capital Region (NCR) Cordillera Administrative Region (CAR) Region I - Ilocos Region Region II - Cagayan Valley Region III - Central Luzon Region IV-A - CALABARZON Region IV-B - MIMAROPA Region V - Bicol Region Region VI - Western Visayas Region VII - Central Visayas Region VIII - Eastern Visayas Region IX - Zamboanga Peninsula Region X - Northern Mindanao Region XI - Davao Region Region XII - SOCCSKSARGEN Caraga Autonomous Region in Muslim Mindanao (ARMM)

Analysis unit

Individual or Person Persons 15 years old and over

Universe

The survey covered all household members of the sample households.

Considered as members of a household are:

a. Persons who are present at the time of visit, whose usual place of residence is the sample household regardless of their length of stay in the household;

b. Persons who are present at the time of visit, whose usual place of residence is outside the sample household but have stayed temporarily with the sample household, for at least 30 days;

c. Persons who are present at the time of visit, whose usual place of residence is outside the sample household but have stayed with the sample household even for less than 30 days, provided that they have been away from their usual place of residence for 30 days or more;

d. Persons who are not present at the time of visit, but are expected to return within 30 days from date of departure to their usual place of residence, which is the sample household; and

e. The following family members who are away at the time of visit:

 1 . Overseas contract workers (OCWs);

 2. Other overseas Filipino workers who have been away for not more than five years from the date of departure, and are expected to be back within five years from the date of last departure;

 3. Employees in Philippine embassies, consulates and other missions; and

 4. Students abroad/tourists who have been away for one year or less and are expected to be back within a year from the date of departure. This category also includes those attending training abroad, medical treatment and missionaries.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2013 Master Sample for household-based survey:

In order to be more effecient in the conduct of household based-surveys, the PSA designed a master sample consists of randomly assigned and selected set of geographic areas with non-overlapping and discernable boundaries known as the primary sampling units (PSUs). The primary sampling unit (PSU) can be (1) the whole barangay, or (2) a portion of a large barangay, or (3) combinations of small barangays.

Provinces and Highly Urbanized Ciities as Sampling Domain

To provide sub-national or provincial level statistics with precise estimates the 2013 MS has 117 major domains as follows: 81 provinces (including the newly created province Davao Occidental); 33 highly urbanized cities (HUC) (including 16 citiies in the National Capital Region; and 3 other areas (Pateros, Isabela City, and Cotabato City).

Primary Sampling Units

In the 2013 MS design each sampling diomain(i.e., province/HUC is divided into exhaustive and non-overlapping area segments known as Primary Sampling Units (PSUs) with about 100 to 400 households. Thus, a PSU can be a barangay/Enumeration Area (EA) or a portion of a large barangay or two or more adjacent small barangays/EAs. The PSUs are then ordered according to the following: (1) North-South/West-East Geographic location; (2)decreasing proporion of households with overseas workers; and (3) decreasing wealth index.

Replicates

From the ordered list of PSUs, all possible systematic samples of 6 PSUs will be drawn to form a replicate for the most of the province domain i.e., 75 out of 81 provinces while all possible systemmatic sample of 8 PSUs will be drawn to form a replicate for most of the HUCs, i.e., 31 of 33 HUCs. Small province domains such as Guimaras, Siquijor, Camiguin, Apayao, and Dinagat Isalnds will have 3 PSUs per replicate. Batanes with very less PSUs formed will have 3 PSUs per replicate but will be covered twice a year only (i.e., January and July rounds only). For other HUCs, San Juan City and Lucena City will have 3 and 5 PSUs per replicate, while the other urban areas, Pateros, and City of Isabela will also have 3 PSUs per replicate while Cotabato City will be allocated with 5 PSUs per replicate.

For instance, in Cagayan with 1008 PSUs formed, a total 1008/6 = 168 possible systematic samples of size 6 or 168 R groups or replicates can be made. The 168 replicates formed are then sorted at random so that the first 4 replicates will be in the first round, next 4 in the second round, and so on.

Sample Allocation Scheme

For each domain, a total of 4 sample replicates will be allotted for each survey round. However, the total number of sample SSUs will be alloted proportionately to the measure of size of the PSU. Thus, a PSU with only 100 households would have less number of samples households than PSUs with 400 households but on the average there will be 12 sample households allotted for each PSU in HUCs and an average of 16 sample households alloted for every PSUs in province domains.

A total national sample of 42,768 sample households (rounds with Batanes sample) or 42,576 sample households (rounds without Batanes sample) will be allotted per survey round.

Mode of data collection

Face-to-face [f2f]

Research instrument

ISH FORM 2 (LFS questionnaire) is a four-page, forty three-column questionnaire that is being used in the quarterly rounds of the Labor Force Survey nationwide. This questionnaire gathers data on the demographic and economic characteristics of the population.

On the first page of the questionnaire, the particulars about the geographic location, design codes and household auxiliary information of the sample household that is being interviewed are to be recorded. Certifications by the enumerator and his supervisor regarding the manner by which the data are collected are likewise to be made on this page.

The inside pages of the questionnaire contain the items to be determined about each member of the sample household. Columns 2 to 10 are for the demographic characteristics; columns 2 to 5A are to be ascertained of all members of the household regardless of age. Columns 6 to 7 are asked for members 5 years old and over, while column 8 is asked for members 5 to 24 years old, column 9 to 10, for 15 years old and over, while columns 11 to 15 are asked for members 5 years old and over. Columns 18 to 42 on the other hand, are the series of items that will be asked of all the members 15 years old and over to determine their labor force and employment characteristics.

Other Relevant Information: The question on hunger experienced by any member of the family because they did not have food to eat, was asked to the head of the household. If in question A, the answer is Yes the frequency of experiencing hunger was asked in question B.

Most of the questions have pre-coded responses. The possible answers with their corresponding codes are printed at the bottom of the page for easy reference. Only the appropriate codes need to be entered in the cells.

Other items, however, require write-in entries such as column 14 (primary occupation) and column 16 (kind of business/industry), etc. For such items, it is required that the enumerator describes the primary occupation or kind of business/industry.

The ISH Form 2 is provided as Technical Documents.

Cleaning operations

Data Processing

Verification and review of questionnaires

The SRs were expected to have verified the completeness of the questionnaires, correctness of the entries, consistency of the entries in the different related items, and the correctness of the codes that were entered in the boxes before the questionnaires were submitted to the Assistant Provincial Supervisor or the Provincial Supervisor. Use the list of sample barangays/EAs provided for coding the region, provinces, municipalities and barangays.

The Assistant Provincial Supervisor or the Provincial Supervisor. upon receipt of the questionnaires reviewed the forms and code the responses for occupation

The data underlying the public sector finances statistical bulletin are presented in the tables PSA 1 to 10.

Abstract

The 2013 Survey on Information and Communication Technology (SICT) is one of the designated statistical activities undertaken by the Philippine Statistics Authority (PSA) to collect and generate information on the availability, distribution and access/utilization of ICT among establishments in the country.

The objectives of the 2013 SICT is to provide key measures of ICT access and use among establishments which will enable the assessment and monitoring of the digital divide in the country. Specifically, the survey aims to measure the following: - component of ICT resources and their utilization by establishments; - diffusion of ICT into establishments from various sources; - e-commerce transactions from data on e-commerce sales/revenue and purchases; - cellular mobile phone business transactions from data on sales/revenue; - estimate of the number of ICT workers in establishments; - methods of disposal of ICT equipment.

The SICT 2013 was a rider survey of the 2013 Annual Survey of Philippine Business and Industry.

Geographic coverage

Regional - "core" ICT and BPM industries are the regions National - "non-core" ICT industries

Analysis unit

An establishment, which is defined as an economic unit under a single ownership or control, i.e., under a single legal entity, engaged in one or predominantly one kind of economic activity at a single fixed location

Universe

The 2013 Survey on Information and Communication Technology (SICT) of Philippine Business and Industry covered all industries included in the 2013 Annual Survey of Philippine Business and Industry (ASPBI).

For the purpose of the survey, these industries were classified as core ICT industries and non-core ICT Industries. Core ICT industries were industries comprising the Information Economy (IE). The Information Economy is a term used to describe the economic and social value created through the ability to rapidly exchange information at anytime, anywhere to anyone. A distinctive characteristic of the information economy is the intensive use, by businesses of ICT for the collection, storage, processing and transmission of information. The use of ICT is supported by supply of ICT products from an ICT-producing sector through trade.

Information Economy is composed of the Information and Communication Technology Sector and Content and Media Sector. Industries comprising these two sectors are as follows: 1) Information and Communication Technology - ICT manufacturing industries - ICT trade industries - ICT service industries: - Software publishing - Telecommunication services - Computer programming, consultancy and related services - Data processing, hosting and related activities; web portals - Repair of computers and communication equipment 2) Content and Media - Publishing activities - Motion picture, video and television programme production, sound recording and music publishing activities - Programming and broadcasting activities

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2013 SICT utilized the stratified systematic sampling design with five-digit PSIC serving as industry strata (industry domain) and the employment size as the second stratification variable.

There were only two strata used for the survey, as follows: TE of 20 and over and TE of less than 20.

The industry stratification for the 2013 SICT is the 5-digit PSIC for both the core ICT industries and for the non-core ICT industries. It has the same industry strata as that of the 2013 ASPBI.

Establishments engaged in the core ICT industries were completely enumerated, regardless of employment size.

The establishments classified in the non-core ICT industries and with total employment of 20 and over were covered on a 20 percent sampling basis for each of the industry domain at the national level. The minimum sample size is set to 3 establishments and maximum of 10 establishments per cell (industry domain).

However, when the total number of establishments in the cell is less than the set minimum sample size, all establishments in that cell were taken as samples.

Mode of data collection

Mail Questionnaire [mail]

Research instrument

The scope of the study includes: - general information about the establishment - information and communication technology (ICT) resources of the establishment - network channels - use of ICT resources, Internet - website of the establishment - e-commerce via internet - e-commerce via computer networks other than the internet - use of mobile phones in selling and other business operation - purchase and disposal of ICT equipment

Cleaning operations

Manual processing took place in Provincial Offices at a number of stages throughout the processing, including: - coding of some data items - editing of questionnaires - checking completeness of entries - consistency check among variables.

Data processing was done in Field Offices and Central Office.

Field Offices were responsible for: - online data encoding and updating - completeness and consistency edits - folioing of questionnaires.

Central Office was responsible for: - online validation - completeness and consistency checks - summarization - tabulation.

Response rate

The overall response rate for the 2013 SICT was 87.04 percent (9,562 of the 10,986 sample establishments). This included receipts of "good" questionnaires, partially accomplished questionnaires, reports of closed, moved out or out of scope establishments. Sample establishments under core ICT industries reported 89.96 percent response rate ( 5,421 out of 6,026 establishments) while non-core ICT industries response rate was 83.48 percent (3,633 out of 4,352 sample establishments). On the other hand, industries classified in Business Process Management (BPM) had a response rate of 83.55 percent (508 out of 608 establishments).

Sampling error estimates

Not computed

Data appraisal

Data estimates were checked with those from other related surveys or administrative data.

Evaluation metrics results (Dice, mIoU, mPA, accuracy, FLOPs, and Params) of various models.

Evaluation metrics results (Dice, mIoU, mPA, and accuracy) of the four network models on the test set before and after denoising (bold indicates best results).

Additional evaluation metrics results (Dice, mIoU, mPA, and accuracy) including UNet-CBAM and UNet-SE.

Preliminary figures between January to September 2024 indicated that ischaemic heart disease was the leading cause of death in the Philippines. The number of people who died from this illness was estimated at 75,500. Following this, cancer resulted in the deaths of about 43,000 people. Eating habits Heart diseases have been linked to high meat consumption, among others. In the Philippines, pork has been the most consumed meat type, followed closely by chicken. While pork meat is typically produced domestically, the country also imports pork to supplement its supply. However, plant-based food has started gaining popularity among Filipinos. In fact, a 2024 survey revealed that 69 percent of surveyed Filipinos consumed plant-based products, including meat alternatives. Common diseases in the Philippines Aside from heart and cerebrovascular diseases, the Filipino population is also exposed to infections, diabetes, skin diseases, and illnesses resulting from high meat consumption. In 2020, over 700,000 Filipinos contracted acute respiratory tract infections, followed by over 400,000 diagnosed with hypertension. In areas with high exposure to rain, dengue infections and leptospirosis have also become prevalent.